Ph.D, M.Tech

Dr. S. Ravishankar currently serves as Chairperson and Professor at the department of Electrical and Electronics Engineering, Amrita School of Engineering, Bengaluru.  He successfully defended his Ph. D. in Single Frame Super Resolution: Some New Approaches.

AREA OF INTERESTS: VLSI for Imaging Application, Pattern Analysis & Recognition, Adaptive Signal Processing, Estimation & Detection, Machine Vision


Publication Type: Conference Paper

Year of Publication Publication Type Title


Conference Paper

M. S. Oommen and Dr. S. Ravishankar, “FPGA implementation of an advanced encoding and decoding architecture of polar codes”, in 2015 International Conference on VLSI Systems, Architecture, Technology and Applications, VLSI-SATA 2015, 2015.[Abstract]

Polar code, newly formulated by Erdal Arikan, has got a wide recognition from the information theory community. Polar code achieves the capacity of the class of symmetric binary memory less channels. In this paper, we propose efficient hardware architecture on a FPGA platform using Xilinx Virtex VI for implementing the advanced encoding and decoding schemes. The performance of the proposed architecture out performs the existing techniques such as: successive cancellation decoder, list successive cancellation, belief propagation etc; with respect to bit error rate and resource utilization. © 2015 IEEE.

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Conference Paper

Dr. S. Ravishankar, Hariharan, S., and V. Kumar, N., “A reliable anti-counterfieting technique using lossless code”, in Proceedings of the 2010 International Conference on Image Processing, Computer Vision, and Pattern Recognition, IPCV 2010, Las Vegas, NV, 2010, vol. 1, pp. 222-226.[Abstract]

In today's modern era, networking primarily through internet plays a vital role in commercial applications, suck as internet banking, e-commerce, internet shopping etc. It becomes necessary in such applications to provide security to our confidential information that gets exchanged through these insecure channels. Our present work intends to hide and protect such sensitive information in an arbitrary background image without the sensitive data being exposed to public domains. Though many techniques exist for this purpose, our proposed method differs by embedding encoded sensitive information on a cover image, compressed and then transmitted to the destination. This provides greater security to the data transmission. This paper critically discusses the advantage of using Arithmetic coding technique and Bit Plane Substitution to derive the stego image. A detailed study is made to compare our technique with other prominent techniques like DCT and DWT. More »»


Conference Paper

S. Balsubramanian, R. Iye, P., and Dr. S. Ravishankar, “Mark sheet verification”, in 2009 3rd International Conference on Anti-counterfeiting, Security, and Identification in Communication, ASID 2009, Hong Kong, 2009.[Abstract]

Today's mark sheets/transcripts issued by the universities/institutions are neither standardised nor secure. In this paper a new method of generating mark sheets under a standardised framework with inbuilt protection has been suggested. This new approach employs 2D Barcode for machine reading capability, Reverse Asymmetric Cryptography to authenticate all the critical fields, OCR for automated verification of the correctness of each and every entry in the mark-sheet. The innovation introduced is in use of all the above technology options optimally to realize a line verification capability of the contents, with practically no limit in the size of the contents to be verified, with full retrieval capability of the full data and automated verification without a on-line look-up to the database and eliminating human error at the verification end. More »»

Publication Type: Journal Article

Year of Publication Publication Type Title


Journal Article

A. P. Navami and Dr. S. Ravishankar, “Degraded document image restoration”, International Journal of Applied Engineering Research, vol. 10, pp. 26509-26519, 2015.[Abstract]

Recovering of text details from degraded images is a difficult task due to high inter or intra variations between the foreground text and the background. The goal of document image restoration is to recover an actual image from the degraded image. In the proposed work, document image restoration based on Background Estimation and Expectation-Maximization algorithm is implemented using Matlab 2008b. Expectation Maximization algorithm estimates the parameters of the Gaussian Mixture Model and then extract the text data from the background based on Maximum Likelihood Estimation. The method shows less sensitivity to background noise and more sensitivity to the text details. The proposed method is performed and evaluated on various types of degraded document images with considerable background noise and different illumination conditions. The results of the proposed method show better performance over similar works reported in the current literature. © Research India Publications.

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