Qualification: 
Ph.D
s_veni@cb.amrita.edu

Dr. S. Veni joined Amrita Vishwa Vidyapeetham as a faculty in the year 2001 under the Department of Electronics and Communication Engineering with 8 years of experience in the field of teaching. She is currently working as Associate Professor. She received her AMIE degree from Institution of Engineers, Calcutta in the year 1994 and M.E degree (Applied Electronics) from Bharathiar University, Coimbatore in the year 1998. She obtained her Ph.D degree in the area of Image Processing from Amrita Vishwa Vidya Peetham in January 2012. Her areas of interest include Signal and Image Processing, hardware implementation of signal and image processing algorithms. She has published nearly 30 papers in International Journals and conferences. Also, she has guided more than 30 projects for both PG and UG students. She has received best paper award four times for the papers she had presented in the conferences and also cash awards from Amrita Vishwa Vidyapeetham, for her publications. She is an Associate Member in the Institution of Engineers, Member in ISTE, Member in IETE, BOS member, Doctoral Committee member (Amrita Vishwa Vidyapeetham and Anna University), Academic Community Member in International Congress for global Science and Technology (ICGST). She has served as a reviewer and session chair in the International conferences, reviewer in reputed journals like Inderscience, IET Image Processing and also as an expert member for the faculty recruitment process held at engineering colleges outside Amrita. She has delivered nearly 10 invited lectures in various Engineering and Polytechnic colleges. She has organized several national workshops in association with CoreEl Technologies, Bangalore and ISRO sponsored national seminar. She has been the Co-Ordinator for M.Tech Communication Engineering and signal Processing from 2014-2016.

Project Contest:

The project titled “Hexagonal Pixel Grid Modeling For Edge Detection and Image Skeletanization”  has been selected and presented for  the Innovate design contest  organized by  Altera and BITS Pilani  during April 2007. Altera Quartus FPGA board worth Rs.25000/- was received as prize.

Research Expertise

To pursue the research in the following fields of interest through funded projects, guiding UG/PG/Ph.D students

  • Developing a real time compressive sensing system for signal and Image Processing applications
  • Developing active learning methods and classification techniques for Hyper Spectral Image Processing
  • Developing Technology for Agriculture  which includes Signal and Image Processing
  • Hardware Implementation of Signal and Image Processing Algorithms
  • Hexagonal Image Processing

UG / PG Student Projects

  1. Lane detection of Images using Hough transform
  2. Efficient Image segmentation during uneven illumination
  3. Hardware Implementation of EZW algorithm
  4. Hardware Implementation of circular Hough Transform
  5. Hardware Implementation of Bio retinal image Encoder
  6. Shape matching for Object in complex images
  7. Edge detection and segmentation using Gabor filters
  8. Hardware implementation of Hexagonal pixel grid modeling for edge detection
  9. Hardware implementation of Hexagonal pixel grid modeling for skeletonization
  10. Design of  Cellular array processor using Hexagonal pixel grid modeling for edge detection and skeletonization
  11. Boundary contour system modeling for dynamic compression and image edge enhancement
  12. Color Image compression for Limited Displays using  self organising feature map
  13. Analysis of Interpolation Kernels For Hexagonal Lattices
  14. Multiresolution Image Processing Using Hexagonal Wavelets
  15. Analysis of Edge detection techniques on Rectangular and Hexagonal Sampled Grids

Teaching

  • Image and Video Processing
  • Digital Signal Processing
  • Sparse signal and image Processing
  • Wavelet based Signal Processing and Applications
  • Digital System Design
  • Image Analysis

Workshops Organized

  • Two days ISRO sponsored National seminar on “Techniques and Applications of Hyperspectral Image analysis” during 19-20th April 2016 at Amrita School of Engineering, Coimbatore
  • Two days national level workshop on  “Xilinx Vivado System Generator and Analog Discovery Kit, “ under the agies of  Department of ECE,  Amrita Vishwa Vidyapeetham, Coimbatore in association with CoreEl Technologies, Bangalore during  21-22 Sep 2015
  • Two days National level workshop on “Embedded Design Flow using Xilinx  ZynQ  SoC” under the agies of  Department of ECE,  Amrita Vishwa Vidyapeetham, Coimbatore in association with CoreEl Technologies, Bangalore during 27-28th Feb 2015
  • Two days Hands-on Training on “Signal Processing Applications using Vivado System Generator”  under the agies of  Department of ECE,  Amrita Vishwa Vidyapeetham, Coimbatore in association with CoreEl Technologies, Bangalore during November 10 -11, 2014. 
  • Two days National level workshop on “Signal and Image Processing Applications using Xilinx System Generator” in association with coreEL Technologies, Bangalore during 10-11 April 2014.
  • One day training program for faculty on “Image Processing using Xilinx System Generator” in association with coreEL Technologies, Bangalore on February 14th 2014.
  • Four days IETE sponsored National level workshop on “Advances in Signal and Image Processing“  during May 29th to 2nd June, 2012 at Amrita Vishwa Vidya peetham.
  • Teaching Assistant in the two week ISTE workshop on Basic Electronics conducted by Indian Institute of Technology, Bombay (Under MHRD) from 28th June to 8th July, 2011 at Amrita Vishwa Vidya peetham, Coimbatore

Membership of scientific and professional bodies

  • Board of studies member for the M. Tech Communication Engineering and Signal Processing
  • Doctoral committee member (Amrita Vishwa Vidyapeetham and Anna university)
  • Life Member in ISTE – LM 16259
  • Member in IETE – M174553
  • Associate Member in The Institution of Engineers – AM0893330
  • Academic Community Member in International Congress for Global Science and Technology (ICGST).

Honours and awards

  • Best paper award for the paper titled “Emotion Recognition from Videos Using Facial Expressions, “ International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems (ICAIECES-2016) at SRM University, May 19 - 20, 2016
  • Best paper award for the paper titled, ”Analog VLSI implementation of Cellular Neural Network and its applications to Image Processing,” in the International Conference on Systemics, Cybernatics and Informatics organised by Pentagram Research Centre Pvt  Ltd, Hyderabad during February 12-15, 2004
  • Best paper award for the paper titled “CMOS VLSI implementation of Analog neuron using    PWM technique” in the National Conference on Emerging Trends in VLSI Design and Testing conducted by PSG College of technology during  February 21- 22, 2003
  • Best paper award for the paper titled “Cell locating strategy in personal   communication Networks” at PSG Tech, Coimbatore in the National conference during Feb 2-3, 2001.
  • Cash award for the publications (for three papers) from Amrita Vishwa Vidyapeetham  in the year 2011.

Conferences Attended

  • International Conference on Intelligent sensing and information Processing (ICISIP)” organized by Melbourn University and IEEE, 4-7, Jan 2005
  •  IEEE conference INDICON 2005 at IIT Madras, Chennai during 11-13 Dec 2005.
  • “National Conference on Emerging Trends in VLSI Design and Testing” at PSG College of technology on February 21 and 22, 2003.
  • “National workshop on Computer vision,   Graphics and Image processing” during Feb 15-16, 2002 at Thiagarajar college  of Engg, Madurai.
  • “National conference on Emerging Trends in Engineering Design Automation” during 23, 24th Feb 2001 at MNM Jain Engineering College, Chennai.
  • “National Conference of Advanced Computing “  during Feb 2,3-2001.
     

 Short-term Courses / Training participated in during the past years

  • Attended the complementary seminar – MATLAB & Simulinkfor Engineering Education on 10/02/2015 at Coimbatore under the track “Teaching signal processing & control system Design using MATLAB & Simulink”
  • Workshop on Space Technology and Sponsored Research by VSSC, ISRO, 25th July 2014 at Amrita Vishwa Vidyapeetham
  • Two-week ISTE Workshop on Signals & Systems conducted by Indian Institute of Technology, Kharagpur which was held under the National Mission on Education through ICT (MHRD) from 2nd to 12th January 2014 at Amrita Vishwa Vidya peetham, Coimbatore.
  • Two days National Workshop on “Hands on Training in Signal & Image Processing Applications using Xilinx System Generator” 22nd & 23rd August 2013 at Sri Ramakrishna Engineering College, Coimbatore.
  • ISTE-SRM sponsored short term training programme on “Sparse theory and applications to signal and Image Processing” from 02.05.2013 to 08.05.2013 at Kongu Engineering College, Perundurai, Erode.
  • ‘Research Retreat’ program at Amrita School of Engineering , Amritapuri on March 28th 2012.
  • 33rd ISTE Convention and National Seminar at Kumaraguru College of       Technology, Coimbatore from 27-10 Dec 2003.
  • STTP Programme on “Neural Networks, Fuzzy Logic and its Applications to Information Processing Technology” at RVS College of Engineering, Dindigul from 23 - 27 June 2003.
  • One-day workshop on ‘Teaching-Learning process’ at Karunya Institute, Coimbatore on May 14th, 2000.
  • Two days workshop on ‘Neuro-Fuzzy-Genetic Systems’ organized by kumaraguru Institute of Technology, Coimbatore during 3 - 4 March 2000.
  • One week Faculty Development programme from May 14th to May18th 1999 at Karunya Institute of Technology, Coimbatore organised by Southern Human Resource Development Agency, Chennai.
  • Three days ISTE workshop on ‘Industry-Institution Interaction’ during  22-24th Dec 1994 at Sree Narayanaguru Institute of Technology, Coimbatore.

Guest Lectures delivered

  • Delivered Lecture on “Hardware Implementation of image processing algorithms” on 20/02/2015 at Ahaliya school of Engineering, Palakkad
  • Delivered Lecture on “Hardware implementation of signal and video processing Architecture” in the workshop organized by ECE department on 25.01.2013 at Amrita Vishwa Vidya Peetham, Coimbatore.
  • Delivered Guest Lecture on the topic “Research trends in Image Processing” in the one day workshop on Image processing and applications organized by the Department of ECE and Benchmark Systems, Chennai on 14.09.2012 at Sri Krishna College of Engineering and Technology, Coimbatore.
  • Delivered Lecture on the topic  “Image enhancement in spatial domain and Fourier domain in the IETE sponsored National level workshop on “Advances in Signal and Image Processing “ on May 30th, 2012 at Amrita Vishwa Vidyapeetham, Coimbatore.
  • Delivered Lecture on the topic  “Image Processing and its applications” in a Technical Symposium on 10.08.2009 at C.M.S. college of Science and Commerce, Chinnavedampatti, Coimbatore - 641006
  • Resource person in the National Seminar and delivered Lecture on "Budding Trends in VLSI" at RVS College of Arts and Science, Sulur, Coimbatore on March 5th, 2004
  • Guest lecture delivered in the topic "VLSI Design" at Christ the king Institute of Technology, Coimbatore on 12th august, 2003.
  • Guest lecture delivered on the topic, "Recent Trends in Computer communication      Networks” at Sree Narayanaguru Institute of Technology, Coimbatore on 14th August, 2000
  • Delivered lecture on the topic  “Hemodynamic control using Fuzzy decision  theory” in the national level short term training programme sponsored by AICTE & ISTE held at Karunya Institute of technology, Coimbatore during May 1999.
  • Delivered lecture on the topic “Multichannel ECG pattern analysis using neural    networks” in the national level short-term training programme sponsored by AICTE & ISTE held at Karunya Institute of technology, Coimbatore during May 1999.

Sessions chaired in the conferences

  • Interview Panel Member for faculty recruitment in Ahalia School of Engineering & Technology, Palakkad on 9/5/2014
  • Chaired a session in the International Conference on Women in Computing (AICWIC 2013) between January 9 and 11, 2013 at Amrita Vishwa Vidya Peetham, Coimbatore
  • Chaired a session in the International conference on Machine Vision and Image Processing (MVIP12) organized by Department of Instrumentation and Control Systems Engineering, PSG College of Technology on December 14 & 15, 2012
  • Chaired a session in the National Conference on “Recent trends in Electronics and Communication Engineering” on 7.03.2012 at Ranganathan College of Engineering, Thondamuthur, Coimbatore - 641 109.
  • Chaired a session in the Regional Level Symoposium SNGPC Techmeet 2006 at Sree Narayanaguru Polyechnic College, Madukkarai, Coimbatore on 06.01.2006.

Reviewer

  • International Journal of Biomedical Engineering and Technology (IJBET) – Inderscience
  • International journal of medical imaging and heath informatics
  • IET Image Processing
  • VLSI-SATA 2015, ASE , Bangalore, program committee member and reviewer
  • International Conference on Computational Intelligence in Data Mining, Springer, ICCIDM-2014
  • International conference on power, signals, control and computations January 9-11, 2014, Vidya Academy of science & Technology, Thrissur, Kerala.
  • International conference on Machine Vision and Image processing (MVIP12)  organized by Department of Instrumentation and Control Systems Engineering, PSG College of Technology on December 14 & 15, 2012
  • National conference on “Recent Trends in Communication and Signal Processing”  (RTCSP 2010, RTCSP 2011, RTCSP 2013 and RTCSP 2014) at Amrita Vishwa Vidyapeetham, Coimbatore.
  • International Conference on “Communication Technology and System Design” ICCTSD 2011 and proceedings (Elsevier) at Amrita Vishwa Vidyapeetham

Other Assignments carried out apart from teaching in Amrita from 2001 -2015:

  • Guiding   Ph.D students in the area of  signal and image processing
  • Setting up of DSP hardware lab with Xilinx system generator and related hardware equipments. In connection with this training programs and workshops will be conducted each year. This will enable the students and researchers in executing projects like implementation of signal and image processing algorithms in hardware.
  • Class counselor (2000-2004 Batch), Class Advisor (2004-2008 Batch), Class Advisor and Year Coordinator (2010-2014 Batch)
  • Project coordinator (2008 and 2013)
  • Guided nearly 20 UG and PG projects
  • Digital Lab Incharge (2007-2012)
  • Contributed during NBA committee visit during 2003.
  • NAAC coordinator
  • Discipline committee member during Amritavarsham 2003 and food serving committee member during Amritavarsham 2013
  • Ph. D admission coordinator
  • Member of various committees during Institution day, convocation, Amritotsavam, Gokulashtami celebrations etc.,
  • Contributed in syllabus preparation for M.Tech VLSI Design (2002-2004 Batch), Electronics and Instrumentation Engineering (2004-2008 Batch), M. Tech Communication Engineering and Signal Processing (2014-2016 Batch), M.Tech Computer Vision and Image Processing, B. Tech (2014-2018), M.Tech Automative Electronics (2015-2017)
  • Significant contribution during the commencement of M.Tech VLSI Design in the year 2002 like developing the lab setup, coordinating the projects etc.,
  • Accompanied students to Amritapuri in the year 2010.
  • Accompanied students M. Tech VLSI students for industrial visits in the year 2004
  • Introduced new electives ‘Sparse Signal and Image Processing’ in the B. Tech   curriculum. ‘Image and Video Processing’ and ‘Hexagonal Image Processing’ in the  M. Tech curriculum.
  • Thrust Area Group (TAG) coordinator – Machine Intelligence Group

Publications

Publication Type: Journal Article

Year of Publication Publication Type Title

2017

Journal Article

Kamalaveni V., S. Veni, and A., N. Kutty K., “Improved self-snake based anisotropic diffusion model for edge preserving image denoising using structure tensor”, Multimedia Tools and Applications, pp. 1-32, 2017.[Abstract]


The performance of classifier algorithms used for predictive analytics highly dependent on quality of training data. This requirement demands the need for noise free data or images. The existing partial differential equation based diffusion models can remove noise present in an image but lacking in preserving thin lines, fine details and sharp corners. The classifier algorithms can able to make correct judgement to which class the image belongs to only if all edges are preserved properly during denoising process. To satisfy this requirement the authors proposed a new improved partial differential equation based diffusion algorithm for edge preserving image denoising. The proposed new anisotropic diffusion algorithm is an extension of self-snake diffusion filter which estimates edge and gradient directions as eigenvectors of a structure tensor matrix. The unique feature of this proposed anisotropic diffusion algorithm is diffusion rate at various parts of an image matches with the speed of level set flow. In the proposed algorithm an efficient edge indicator function dependent on the trace of the structure tensor matrix is used. The proposed model performs best in preserving thin lines, sharp corners and fine details since diffusion happens only along edges and diffusion is totally stopped across edges in this model. The additional edge-stopping term which is a vector dot product of derivative of an edge stopping function and derivative of an image computed along gradient and edge orthogonal directions is used in this model as shock filter which enables increased sharpness at all discontinuities. The performance of proposed diffusion algorithm is compared with other classical diffusion filters like conventional perona-malik diffusion, conventional self-snake diffusion methods. © 2017 Springer Science+Business Media New York

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2016

Journal Article

S. Abhishek, S. Veni, and Narayanankutty, K. A., “Improving information content in Compressed Sensing by modifying the random re-construction matrices”, Indian Journal of Science and Technology, vol. 9, 2016.[Abstract]


Background/Objectives: Compressed Sensing (CS) is an efficient sensing paradigm which guarantees reasonable reconstruction with less number of samples. We aim to increase the reconstruction quality of signals in CS. Methods/Statistical Analysis: The behavior of random matrices is analyzed and an efficient method for improving the reconstruction quality is developed in CS based ECG reconstruction applications. The method is compared against Biorthogonal wavelet based approaches. Findings: Our analysis reveals that introduction of a modified column vector in the reconstruction matrix, which contains the sum of all columns of random matrix increases the reconstruction quality in CS applications. This idea was applied to different sparsifying domains and the results are very encouraging. We studied the effect of doing this on the singular values and both unitary matrices U and V. The first singular value (σ) shot up making the condition number high, however there was not much change in the other singular values. The matrix U seems to remain random unitary matrix, where as matrix V has one value becoming unity in its rank space. Application/Improvements: Compared to wavelet based approaches the method shows reasonable improvement in Percentage Root Square Deviation (PRD).

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2016

Journal Article

J. Sethupathy and S. Veni, “OpenCV based disease identification of mango leaves”, International Journal of Engineering and Technology, vol. 8, pp. 1990-1998, 2016.[Abstract]


This paper aims in classifying and identifying the diseases of mango leaves for Indian agriculture. K-means algorithm is chosen for the disease segmentation, and the disease classification and identification is carried out using the SVM classifier. Disease identification based on analysis of patches or discoloring of leaf will hold good for some of the plant diseases, but some other diseases which will deform the leaf shape cannot be identified based on the same method. In this case leaf shape based disease identification has to be performed. Based on this analysis two topics are addressed in this research paper. (1) Disease identification using the OpenCV libraries (2) Leaf shape based disease identification.

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2016

Journal Article

K. Vanjigounder, A, N. K., and S. Veni, “Performance Comparison of Total Variation based Image Regularization Algorithms”, International Journal on Advanced Science, Engineering and Information Technology, vol. 6, no. 4, 2016.[Abstract]


The mathematical approach calculus of variation is commonly used to find an unknown function that minimizes or maximizes the functional. Retrieving the original image from the degraded one, such problems are called inverse problems. The most basic example for inverse problem is image denoising. Variational methods are formulated as optimization problems and provides a good solution to image denoising. Three such variational methods Tikhonov model, ROF model and Total Variation-L1 model for image denoising are studied and implemented. Performance of these variational algorithms are analyzed for different values of regularization parameter. It is found that small value of regularization parameter causes better noise removal whereas large value of regularization parameter preserves well sharp edges. The Euler’s Lagrangian equation corresponding to an energy functional used in variational methods is solved using gradient descent method and the resulting partial differential equation is solved using Euler’s forward finite difference method. The quality metrics are computed and the results are compared in this paper. More »»

2016

Journal Article

S. Abhishek, S. Veni, and Narayanankutty, K. A., “Splines in Compressed Sensing”, International Journal on Advanced Science, Engineering and Information Technology, vol. 6, pp. 469–476, 2016.[Abstract]


It is well understood that in any data acquisition system reduction in the amount of data reduces the time and energy, but the major trade-off here is the quality of outcome normally, lesser the amount of data sensed, lower the quality. Compressed Sensing (CS) allows a solution, for sampling below the Nyquist rate. The challenging problem of increasing the reconstruction quality with less number of samples from an unprocessed data set is addressed here by the use of representative coordinate selected from different orders of splines. We have made a detailed comparison with 10 orthogonal and 6 biorthogonal wavelets with two sets of data from MIT Arrhythmia database and our results prove that the Spline coordinates work better than the wavelets. The generation of two new types of splines such as exponential and double exponential are also briefed here .We believe that this is one of the very first attempts made in Compressed Sensing based ECG reconstruction problems using raw data. More »»

2015

Journal Article

A. J. Thottupattu, Neha, S., and S. Veni, “Hardware software co-simulation of IIR filter using Xilinx system generator for FPGA implementation”, International Journal of Applied Engineering Research, vol. 10, pp. 37151-37155, 2015.[Abstract]


This paper proposes a method for implementing a Butterworth IIR low pass filter on Xilinx Spartan-6 XC6SLX45 FPGA board. The FPGA implementation is preferred because of increased computational speed compared with implementation in DSP processors. The IIR filter coefficients are calculated manually and the direct form II structure was simulated on Simulink with Xilinx block sets. In addition to simulation, hardware/software co-simulation was performed and it was observed that similar results were obtained. © Research India Publications.

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2014

Journal Article

L. Nagaraj, .Varshini, M., K.R, M., Sreenesh, B., .Sivakumar, V., and S. Veni, “Compressed sensing system for efficient ECG signal compression”, International Journal of Research in Engineering and Technology, vol. 3, no. 7, 2014.[Abstract]


Compressed sensing (CS) is a novel idea wherein a signal can be sampled at sub-Nyquist rates and still be effectively reconstructed. Many natural signals such as the ECG signal are sparse and have sparse representation when expressed in a suitable basis. Compressed sensing exploits the sparsity by acquiring a small number of projections on to random vectors which are sufficient to recover the signal. This theory enables an effective implementation of patient-centric telecardiology or mobile cardiology systems. It guarantees improvement in performance by drastically reducing the number of samples that requires to be either stored or transmitted. Specifically in the context of ECG monitoring systems, CS signal acquisition revolutionizes miniaturization of the hardware and improves its energy efficiency. This work proposes to create a Compressed sensing based mathematical framework for the acquisition and recovery of an ECG signal which has been further classified into normal and abnormal categories. During the compression stage, a sensing matrix which results in a low PRD (Percentage root mean square distortion) is used and an efficient reconstruction algorithm is employed to retrieve the most valuable information from the ECG signal. The classification of the ECG signal is done by studying the region of interest i.e. the QRS complex. The heart rate , the interval between two R peaks and the amplitude of the R peaks contributes chiefly to determining an abnormality in the ECG signal. This model can be implemented with a wireless body sensor network (WBSN) which may be used to alert a doctor in emergency situations. More »»

2014

Journal Article

S. Veni and Vinod, S., “Hardware Implementation of Hexagonal Sampling based Bio-Inspired Retinal Encoder (Accepted)”, International Journal on Signal and Imaging Systems Engineering, Inderscience (Scopus indexed), 2014.

2014

Journal Article

S. Veni and Narayanankutty, K. A., “Vision-based hexagonal image processing using Hex-Gabor”, Signal, Image and Video Processing, vol. 8, pp. 317–326, 2014.[Abstract]


About 97{%} receptive field of the neurons is very closely described as 2D Gabor wavelet and it is mostly suitable for vision system modeling. Immense work is available on texture information, especially for rectangular structures. However, there is a little work in recognizing minute details in an image on hexagonal structure by either interpolation or enhancement. In this work, the two important operations of biological visual system such as enhancement and interpolation are performed using the Hex-Gabor process. It is possible to obtain an error-free image at sigma = 2/pi using the proposed Hex-Gabor process and the significance of this sigma value is proved. For the performance analysis standard reflected images and X-ray images are considered. More »»

2013

Journal Article

S. Aiswarya and S. Veni, “Hardware Implementation of EZW based Image Compression with Huffman coding”, International Journal of Engineering Science and Innovative Technology (IJESIT), vol. 2, no. 5, pp. 437-445, 2013.[Abstract]


Embedded Zero-tree Wavelet (EZW) is a wavelet based image compression scheme. It is basically a quantization stage that incorporates some characteristics of the wavelet decomposition. The EZW approach and its descendants significantly outperform some of the generic approaches. The wavelet coefficients in different sub bands represent the same spatial location in the image. This is an important characteristic used by EZW. In case of decomposition, since the size of the different sub bands is different, then a single coefficient in the smaller sub band may represent the same spatial location as multiple coefficients in the other sub bands. This paper describes hardware implementation of EZW encoding algorithm along with Huffman encoding and decoding architectures. After performing lifting based DWT technique and EZW algorithm, Huffman coding ensures further compression of the image. In Huffman coding no bit string is a prefix of any other bit string. Hence each code is uniquely decodable.

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2012

Journal Article

S. Veni, “Vision based hexagonal image processing”, 2012.[Abstract]


About 97% receptive field of the neurons is very closely described as 2D Gabor wavelet and it is mostly suitable for vision system modeling [8]. Immense work is available on texture information, especially for rectangular structures [37- 40]. However, there is a little work in recognizing minute details in an image by either interpolation or enhancement. Hexagons have many advantages namely six fold symmetry, well behaved connectivity, improved angular resolution, storage savings, computational speed, and circular 7-pel shape. In the tessellations with Hexagons, if v is spatial domain lattice, then frequency domain lattice or reciprocal lattice v~ is obtained as v = 2π (v −1)T ). The basis vectors in the two domains are seen to be mutually orthogonal, which is due to the fact that the Fourier transform is an orthogonal projection. In the past years, there had been many attempts in representing hexagons in the regular square lattice or in a Spiral Addressing Scheme (SAS) [13-34]. Regular geometry is only kept in the case of SAS, however processing such pseudo lattices gave rise to better results compared with square lattices. This research work started with implementation of above mentioned hexagonal pseudo lattices and later entered on a real hexagonal lattice through the Hex - spline process described by D. Van De Ville et al. [45]. Hex-spline process is a structure where regular hexagon can be represented and it is basically used for interpolation. Filtering the images was attempted by Gabor kernels in hexagonal domain in different orientations, on this type of structure. As the orthogonal directions of the Gabor filter in the three directions ( 00, 600, 1200 ) are converged between three adjacent pixels, it was considered important to filter out the images in these directions. A low pass filter and high pass filter may be used to enhance surface information and edge information respectively. When the kernels are placed on image pixel locations and add, it is not only giving just image enhancement, but also facilitates interpolation. This is because, as the sigma values in a Gabor 23 filter reduce, the Gaussian envelope covers only a part of a wave of the modulating sinusoids, to render a low-pass characteristic to the filter. While the low-pass component is predominant, the edge enhancement part is still present in the three orthogonal directions as additional nonlinearity in the kernel. More »»

2011

Journal Article

S. Veni, .A.Narayanankutty, K., and Raffi, M., “Hardware Implementation of Edge detection on Hexagonal Sampled Image Grids”, International Journal of Computer Applications (0975 - 8887), vol. 24, 2011.[Abstract]


Increasing Processing capabilities of graphic devices and recent improvements in CCD technology have made hexagonal sampling attractive for practical applications. Also, hexagonal representation has special computational features that are pertinent to the vision process. This paper describes Edge detection operation on hexagonally sampled images and its hardware implementation based on Cellular Logic Array Processing (CLAP) algorithm. This architecture builds up a virtual hexagonal grid system on the memory space of computer and processing algorithms can be implemented on such virtual spiral space, thereby decreasing the computational complexity. These operations were done on hexagonal sampled grid using MATLAB version 7 and the results were compared with rectangular sampled grid. MODELSIM and Quartus II software were used for analysis and synthesis. The performance was tested using Altera Cyclone II FPGA. It was observed from the results that there is a marginal improvement while processing with hexagonal sampled grid. Hardware utilization is found to be less for the image sampled on hexagonal grid compared with rectangular grid. General Terms Image processing, Edge detection, VLSI architecture. Keywords Hexagonal image processing, CLAP algorithm, FPGA implementation of CLAP algorithm. More »»

2011

Journal Article

S. Veni and Narayanankutty, K. A., “Gabor Functions for Interpolation on Hexagonal Lattice”, International Journal of Electronics & Communication Technology (IJECT), vol. 2, no. 1, 2011.[Abstract]


An interpolation model using Gabor Filter is demonstrated on hexagonally sampled data, which outperform classical B-splines and MOMS. Our method has optimal approximation theoretic performances, for a good quality image. The computational cost is considerably low when compared to similar processing in the rectangular domain. In this paper the parameter sigma of 2/pi is found to satisfy most of the image interpolation requirements in terms of high Peak Signal-to-Noise Ratio (PSNR) , lower Mean Squared Error (MSE) and better image quality by adopting a windowing technique. More »»

2009

Journal Article

S. Veni, Narayanankutty, K. A., and Kirankumar, M., “Design of Architecture for Skeletonization on Hexagonal Sampled Image Grid”, International Journal on Graphics, Vision and Image Processing (ICGST-GVIP), vol. 9, no. 1, 2009.[Abstract]


ABSTRACT This paper describes skeletonization and reconstruction operation of binary image using synchronous processor array based on hexagonally sampled images . A modified architecture using the principle of Hilditch's algorithm was constructed using synchronous processing elements on hexagonal grid. Based on the architecture for rectangular skeletonization operations, an algorithm for reconstruction is designed, which is a new attempt. The processing elements connected in rectangular array and hexagonal array were investigated. Hexagonal reconstruction gave superior results, in terms of time and performance. For hardware implementations, we have used Modelsim for simulation, Quartus II Software for analysis and synthesis. The performance was tested using Altera Cyclone II FPGA. It was observed that hardware utilization is found to be less for the image sampled on hexagonal grid than on rectangular grid. More »»

Publication Type: Conference Proceedings

Year of Publication Publication Type Title

2017

Conference Proceedings

R. Anand, S. Veni, and Aravinth J., “Big Data Challenges in Airborne Hyperspectral Image for Urban Landuse Classification”, 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI). 2017.[Abstract]


In recent years, it was a difficult task to classify a huge set of data due to the increasing population in urban places. As of now, satellite hyperspectral image provides information but this is not sufficient to classify data in urban areas. To develop the urban areas, accurate and timely information is necessary for the government. Hence, airborne hyperspectral data provides sufficient information for urban planning and disaster management. This paper, focuses on the following objectives: (i) To improve the classification accuracy in bigdata images (ii) To reduce the mixed pixels in residential buildings that are surrounded by small trees (iii) To bring down similar pixels of roads and parking lots. In this paper, 15 different classes were classified which are important for the growth in urban areas. The SVM classifier has more accuracy and better kappa coefficient compared with Neural Network (NN) and K-Means clustering. The Overall Accuracy (OA) has improved by 23.3.

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2016

Conference Proceedings

R. Anand, S. Veni, and Aravinth J., “An Application of image processing techniques for Detection of Diseases on Brinjal Leaves Using K-Means Clustering Method”, IEEE International Conference on Circuit, Power and Computing Technologies”, ICCPCT. 2016.

2016

Conference Proceedings

S. Abhishek, S. Veni, and Narayanankutty, K. A., “Exponential-Splines in Compressed Sensing ECG Reconstruction”, International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems (ICAIECES-2016) . SRM University, 2016.

2016

Conference Proceedings

T. Selvi P, P, V., R, J., Srikumar, S., and S. Veni, “Emotion Recognition from Videos Using Facial Expressions”, International Conference on Artificial Intelligence and Evolutionary Computations in Engineering Systems (ICAIECES-2016) . SRM University, 2016.

2016

Conference Proceedings

Anand R, S. Veni, and Aravinth J., “An Application of image processing techniques for Detection of Diseases on Brinjal Leaves Using K-Means Clustering Method(2016)”, Fifth International Conference on Recent Trends in Information Technology 2016 (ICRTIT 2016). Anna University, Chennai campus , 2016.

2013

Conference Proceedings

S. Veni, Jyothirmayie, P., G. Reddy, O., Vineela, G., Praveenkumar, S., and Srihrsha, V. L. V., “Lane Detection and Departure Warning System”, International Conference on Recent Trends in Engineering and Technology & Mechanics, Simulation and Control (ICRTET 2013) . pp. pp. 125-130, 2013.

2005

Conference Proceedings

S. Veni and Dr. Yamuna B., “Hardware implementation of CNN”, International Conference on Intelligent sensing and information Processing (ICISIP). IEEE , Le Royal Meridian, Chennai, pp. 320-325, 2005.

Publication Type: Conference Paper

Year of Publication Publication Type Title

2017

Conference Paper

J. E. George, Aravinth J., and S. Veni, “Detection of Pollution Content in an Urban Area Using Landsat 8 Data”, in 2017 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2017.[Abstract]


Pollution control is a challenging task in current scenario. The very first step to control pollution is to detect the sources of pollution. The urban areas are more polluted than rural due to the high population density. The pollutants considered in this paper are aerosol and asbestos sheets. The source of asbestos are building roofs which are mainly in urban area and that of aerosol is combustion of coal. The conventional image processing techniques failed to detect the pollutant in urban environment which can be performed well using multispectral imaging. Since each object has different temperatures using the TIR (Thermal Infrared) bands of Landsat 8 data, the urban objects are classified using the land surface temperature map. The presence of asbestos sheets is detected by change in intensity of images with respect to Band 7 (Short Wave Infrared) and Band 9 (Cirrus). Aerosol is comprised of components that cause air pollution. In this work, the PM10 value is considered as one of the measures to identify the concentration of particulate matters in specific area.

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2016

Conference Paper

S. Thushara and S. Veni, “A multimodal emotion recognition system from video”, in 2016 International Conference on Circuit, Power and Computing Technologies (ICCPCT), 2016.[Abstract]


Emotion recognition (ER) systems finds applications in many fields like call centres, humanoid Roberts and robotic pets, telecommunication, psychiatry, behavioral science, educational softwares, etc., In this work, the speech and facial features extracted from the video data is explored to recognize the emotions. Since both these features are compliment to each other, on combining them will result in higher performance. The features used for emotion recognition from video data are geometric and appearance based while prosodic and spectral features are employed for speech signal. Support Vector Machine (SVM) classifier is used to capture the emotion specific information. The basic aim of this work is to explore the capability of speech and facial features to provide the emotion specific information. More »»

2016

Conference Paper

K. A. Das, George, K. K., Dr. Santhosh Kumar C., S. Veni, and Panda, A., “Modified gammatone frequency cepstral coefficients to improve spoofing detection”, in 2016 International Conference on Advances in Computing, Communications and Informatics (ICACCI), 2016.[Abstract]


Voice spoofing is one of the major challenges that needs to be addressed in the development of robust speaker verification (SV) systems. Therefore, it is necessary to develop systems (spoofing detectors) that are able distinguish between genuine and spoofed speech utterances. In this work, we propose the use of modified gammatone frequency cepstral coefficients (MGFCC) on enhancing the performance of spoofing detection. We also compare the effectiveness of GMM based spoofing detectors developed using mel frequency cepstral coefficients (MFCC), gammatone frequency cepstral coefficients (GFCC), modified group delay cepstral coefficients (MGDCC) and cosine normalized phase cepstral coefficients (CNPCC) with that of MGFCC. The experimental results on ASV spoof 2015 database show that MGFCC outperforms magnitude based, MFCC and GFCC, and phase based, MGDCC and CNPCC, features on the known attack conditions. Further, we performed a score level fusion of the systems developed using MFCC, MGFCC, MGDCC and CNPCC. It is observed that the fused system significantly outperforms all the individual systems for known and unknown attack conditions of ASV spoof 2015 database.

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2015

Conference Paper

S. Abhishek, S. Veni, and Narayanankutty, K. A., “A trick to improve PRD during compressed sensing ECG reconstruction”, in Second International Conference on Signal Processing and Integrated Networks (SPIN), 2015 2nd International Conference on, Amity University, Noida, 2015.[Abstract]


In the problem of compressed sensing (CS) successful reconstruction can be achieved by maintaining a low mutual coherence between the columns in the vector space. In this work, a way to increase the mutual incoherence is introduced. This is achieved by replacing certain matrix domain of the sparse random matrix, which is used as the measurement matrix with null space bases. For convenience, this can be replaced even by identity matrices. The result shows that there is a substantial improvement in Peak Root mean Square deviation (PRD). Many different alternatives have been tried out and relative PRD were plotted. Thresholding is generally adapted in CS in order to reduce the PRD values. It was found that without using thresholding technique, it is possible to obtain reduction in PRD values. The time algorithmic performance was also analyzed and found to be better.

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2015

Conference Paper

K. Ka George, Dr. Santhosh Kumar C., Panda, Ab, Raji Ramachandran, Das, K. Aa, and S. Veni, “Minimizing the false alarm probability of speaker verification systems for mimicked speech”, in 2015 International Conference on Computing and Network Communications, CoCoNet 2015, 2015, pp. 703-709.[Abstract]


Speaker verification (SV) systems need to be robust to mimicked voices of target speakers as non-target trials to make them usable in critical applications. However, the performance of SV systems for mimicked voice test conditions has not been extensively explored. © 2015 IEEE.

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2014

Conference Paper

S. Veni and Sarika, K., “Hardware Implementation of Hough Transform for Circle Detection (Submitted)”, in International Conference on Interdisciplinary Advances in Applied Computing (ICONIAAC ’14) , Amrita School of Engineering, Coimbatore , 2014.

2011

Conference Paper

S. Veni, Murugan, S. S., and Natarajan, V., “Modified LMS adaptive algorithm for detection of underwater acoustic signals against ambient noise in shallow water of Indian sea”, in 2011 International Conference on Recent Trends in Information Technology (ICRTIT), 2011.[Abstract]


In the underwater communication, the biggest challenge is to reduce the masking effect of underwater ambient noise. The main objective of this paper is to develop an optimum modified LMS adaptive algorithm for accurate detection of underwater acoustic signal, which is prone to the effect of ambient noise in the near and far seas. Comparative analyses on various algorithms are performed. This modified LMS algorithm is found better than the other existing algorithms with respect to the Signal to Noise Ratio (SNR) and Mean Square Error (MSE). For this analysis, data collected using passive Sonar at a depth of 5 meters in shallow water region. More »»

2011

Conference Paper

S. Veni, S. Murugan, S., and Radha, S., “Adaptive algorithm for detection of underwater acoustic signals against ambient noise in shallow water at Indian seas”, in 2011 International Conference on Emerging Trends in Electrical and Computer Technology, 2011.[Abstract]


Effective underwater communication can be carried out when the masking effect of underwater ambient noise is reduced. The main objective of this paper is to develop an optimum adaptive algorithm for accurate detection of the underwater acoustic signal buried due to the effect of ambient noises in the near and far seas. A comparative analysis on various algorithms using MATLAB is performed and to validate its performance the signal to noise ratio is calculated. For this analysis the data collected using passive Sonar at Chennai at a depth of 5metre in shallow water region is considered. More »»

2011

Conference Paper

S. S. Murugan, Natarajan, V., S. Veni, and Balagayathri, K., “Analysis of adaptive algorithms to improve the SNR of the acoustic signal affected due to wind driven ambient noise in shallow water”, in 2011 International Symposium on Ocean Electronics, 2011.[Abstract]


Underwater signal transmission is a challenging task since the usable frequency range is limited to low frequency and the transmission of electromagnetic waves is impossible due to its high attenuation nature. Hence low frequency acoustic signal is more suited for transmission in underwater. Underwater transmission is highly affected by wind noise which is predominant at low frequency. The real time data collected from Indian Seas at Chennai (Bay of Bengal) are studied in detail using Welch, Bartlett and Blackman estimation methods and the results shows the effect of wind over 0-8 kHz range. Various adaptive algorithms are analyzed in detail and the Signal to Noise Ratio (SNR) values are tabulated for different wind speeds. The results shows that Recursive Mean Square (RLS) works better when compared to others. The maximum Signal to Noise Ratio (SNR) of about 42-51 dB is achieved. More »»

2009

Conference Paper

S. L. Reddy, Vidya, P., S. Veni, and Narayanankutty, K. A., “Wavelet Based Edge Detection and Multiresolution Analysis on Hexagonal Sampled Grid using Interpolation”, in International conference on Signal and Image Processing (ICSIP 2009), Vidya Vikas Institute of Engineering & Technology, Mysore, 2009.

2008

Conference Paper

S. Veni and A, F., “A Novel Hexagonal wavelet transform”, in Recent Trends in Computational Science" (ICRTCS - 2008), Toc H Institute of Science, Ernakulam, 2008.

2006

Conference Paper

S. Veni, Narayanankutty, K. A., and Senthilnayaki, M., “Hexagonal Pixel Grid Modeling for Edge Detection and Design of Cellular Architecture for Binary Image Skeletonization”, in INDICON 2006, AMALTAS, India Habitat Centre, New Delhi, 2006.

2004

Conference Paper

S. Veni and Dr. Yamuna B., “Analog VLSI implementation of Cellular Neural Network and its applications to Image Processing”, in International Conference on Systemics, Cybernatics and Informatics, Pentagram Research Centre Pvt Ltd, Hyderabad , 2004.

2003

Conference Paper

S. Veni and Madhavan, B. K., “CMOS VLSI implementation of Analog neuron using PWM technique”, in National Conference on Emerging Trends in VLSI Design and Testing, PSG College of Technology, Coimbatore , 2003.

2002

Conference Paper

S. Veni, “Color Image compression for Limited Displays using self organising feature map”, in National workshop on Computer vision, Graphics and Image processing, Thiagarajar College of Engineering, Madurai, 2002.

2001

Conference Paper

S. Veni, “Personal Domain Applications using WAP”, in National conference on Emerging Trends in Engineering Design Automation, MNM Jain Engineering College, Chennai, 2001.

2001

Conference Paper

S. Veni, “Cell locating strategy in Personal Communication Network”, in National Conference of Advanced Computing , PSG College of Technology, Coimbatore, 2001.

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