Qualification: 
M.Tech
v_anupa@cb.amrita.edu

Anupa Vijai currently serves as an Assistant Professor at Department of Computer Science and Engineering, Amrita School of Engineering, Coimbatore. She joined the department in August 2013. She received her M. Tech. in Computer Vision and Image Processing in the year 2012 and B. Tech. in Computer Science and Engineering in the year 2010. Her areas of research include Image Processing and Machine Learning.

Publications

Publication Type: Journal Article

Year of Publication Title

2019

Anupa Vijai, Padmavathi, S., and Venkataraman, D., “Cloud and Shadow Identification from Aerial Images”, International Journal of Innovative Technology and Exploring Engineering, vol. 8, no. 7, pp. 532-536, 2019.[Abstract]


Clouds and shadows pose severe problems in discernment of the scene and identification of objects in aerial photography. The changes in illumination,ensued by the presence of cloud and the shadow,aresome of the reasons that lead to ambiguity, while carrying out image segmentation leading to detection of targeted objects. Conventional methods are efficient in detecting thick clouds in contrastive background, but perform poorly in the perception of thin clouds, multiple clouds and their shadows. Reference images for the input are needed in most cases, and separate algorithms are pursued, to identify clouds and shadows in an image, which might not be feasible in all scenarios. Techniques used in this paperto detect cloud and shadows,obviating the need for reference images, are image enhancement, analysis of color histogram of input images, adoption of automatic thresholding and mathematical morphology on the input image. The proposed algorithm,was found to be fast,and experimented on various images that contained multiple white cloud clusters of different shapes, thickness and their shadows. The algorithmwas validated with an accuracy of 94.6% and 87.2% for identification of clouds and shadows, respectively.

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Publication Type: Conference Proceedings

Year of Publication Title

2016

S. Sreelakshmi, Anupa Vijai, and Dr. Senthil Kumar T., “Detection and Segmentation of Cluttered Objects from Texture Cluttered Scene”, Proceedings of the International Conference on Soft Computing Systems , vol. 398. Springer, pp. 249-257, 2016.[Abstract]


The aim of this paper is to segment an object from a texture-cluttered image. Segmentation is achieved by extracting the local information of image and embedding it with active contour model based on region. Images with inhomogenous intensity can be segmented using this model by extracting the local information of image. The level set function [1] can be smoothened by introducing the Gaussian filtering to the current model and the need for resetting the contour for every iteration can be eliminated. Evaluation results showed that the results obtained from the proposed method is similar to the results obtained from LBF [2] (local binary fitting) energy model, but the proposed method is found to be more efficient in terms of computational aspect. Moreover, the method maintains the sub-pixel reliability and boundary fixing properties. The approach is presented with metrics of visual similarity and could be further extended with quantitative metrics.

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2014

Dr. Senthil Kumar T. and Anupa Vijai, “3D Reconstruction of Face: A comparison of Marching Cube and Improved Marching Cube Algorithm”, Proceedings of the International Conference of Advances in Engineering and Technology, vol. 1. pp. 6-9, 2014.[Abstract]


3D reconstruction of face is one of the advancements in physical modeling techniques which uses engineering methods in the field of medicine.The systems in development propose a software tool that will help in craniofacial surgery. The existing approaches for 3D reconstruction has different applications from real scenary to human parts of body. The analysis of the different algorithms allow developers to make vital decisions in understanding the modelling of the face. The human face has different regions including the tissue and hard bones. The paper presents a comparison of two surface rendering techniques, Marching Cube(MC) and Improved Marching Cube(IMC) algorithms, and draws conclusions for analysing the suitable approach for a specific range of application.

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2012

Dr. Senthil Kumar T. and Anupa Vijai, “3D Reconstruction of Face from 2D CT Scan Images”, Procedia Engineering, vol. 30. pp. 970-977, 2012.[Abstract]


3D reconstruction of face is one of the advancements in physical modeling techniques which uses engineering methods in the field of medicine.The systems in development propose a software tool that will help in craniofacial surgery. The existing approaches for 3D reconstruction has different applications from real scenary to human parts of body. The analysis of the different algorithms allow developers to make vital decisions in understanding the modelling of the face. The human face has different regions including the tissue and hard bones. The paper presents a survey on different 3D reconstruction approaches and draws conclusions for analysing the suitable approach for a specific range of application.

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