Specialization : Image Processing and Computer Vision

Digital image processing is the use of computer algorithms to perform image processing on digital images. It allows a much wider range of algorithms to be applied to the input data and can avoid problems such as the build-up of noise and signal distortion during processing. Computer vision is an interdisciplinary field that deals with how computers can be made for gaining high-level understanding from digital images or videos. From the perspective of engineering, it seeks to automate tasks that the human visual system can do. Computer vision tasks include methods for acquiring, processing, analyzing and understanding digital images. 
The research in this area is focussed on image processing and computer vision,  vision and machine learning, mathematical modelling and analysis of images, low level image processing algorithms, medical image analysis and processing, design and development of computer aided diagnostic systems (CAD), medical image reconstruction, features extraction and selection, pattern recognition and classification,  soft computing, video surveillance, biometrics, video processing, image forensics, and gait recognition.

Sub Areas under Computer Vision:

  • Image Processing, Computer Vision
  • Computer Vision and machine learning
  • Medical image analysis and CAD
  • Low level Image analysis
  • Pattern recognition, Pattern Classification, Soft Computing
  • Video Surveillance
  • Biometrics
  • Information Forensics and Security

Recent Publications:

  • Vibhav Prakash Singh, Subodh Srivastava, Rajeev Srivastava, “Effective Mammogram Classification Based on Center Symmetric-LBP features in Wavelet Domain Using Random Forest Classifier”, Technology and Healthcare, official journal of the European Society for Engineering and Medicine, Vol. 25 (4), pp. 709-727,  2017. DOI: 10.3233/THC-170851 (SCI-0.724).
  • Vibhav Prakash Singh, Rajeev Srivastava, “Improved CBIR System Using Fusion of Fast Features with Varying Weighted Similarity Measure and Random Forest Classifier”, Multimedia Tools and ApplicationsSpringer, 1-26, DOI: 10.1007/s11042-017-5036-8, 2017 (SCI-1.53).
  • Vibhav Prakash Singh, Rajeev Srivastava, “Automated and Effective Content-Based Mammogram Retrieval Using Wavelet Based CS-LBP Feature and Self-Organizing Map”, Biocybernetics and Biomedical Engineering, Elsevier, 2017 (SCI-1.03, Accepted under press).
  • Vibhav Prakash Singh, Subodh Srivastava, Rajeev Srivastava, “An Efficient and Automated Content Based Image Retrieval for Digital Mammography”, Journal of X-Ray science and Technology, Vol. (Preprint), pp.1-20, IOS Press, UK , DOI:10.3233/XST-17306, 2017 (SCI-1.11)
  • Rajesh Kuamr, Subodh Srivastava, Rajeev Srivastava, A Fourth order PDE based Fuzzy C- Means approach for Segmentation of Microscopic biopsy images in presence of Poisson noise for cancer detection, Computer Methods and Programs in Biomedicine, Elsevier, Volume 146, July 2017, Pages 59–68. (SCI IF: 1.862)
  • RB Yadav, Subodh Srivastava, Rajeev Srivastava, "A partial differential equation‑based general framework adapted to Rayleigh’s, Rician’s and Gaussian’s distributed noise for restoration and enhancement of magnetic resonance image", Journal of Medical Physics, Vol. 41, Issue 4, pp. 254-265, 2016. DOI: 10.4103/0971-6203.195190.
  • Arvind Tiwari, Rajeev Srivastava, “An efficient approach for prediction of nuclear receptor and their subfamilies based on fuzzy k-nearest neighbor with maximum relevance minimum redundancy", Proceedings of the National Academy of Sciences, India Section A: Physical Sciences (An International Journal), Springer, Nov’2016. (SCI Indexed).
  • Nagendra Pratap Singh, Rajeev Srivastava, “Retinal blood vessels segmentation by using Gumbel Probability Distribution Function based matched filter”, Computer Methods and Programs in Biomedicine, Elsevier (Science Direct), Volume 129, Pages 40–50, June’ 2016. (SCI IF: 1.897).
  • Alok Kumar Singh Kushwaha, Subodh Srivastava, and Rajeev Srivastava, “Multi-View Human Activity Recognition Based on Silhouette and Uniform Rotation Invariant Local Binary Patterns”, Multimedia Systems, Springer, pp 1-17, March’ 2016, ISSN: 0942-4962 (Print) 1432-1882 (Online) (SCI IF: 0.619), doi: 10.1007/s00530-016-0505-x.
  • Alok K. Singh Kushwaha, Rajeev Srivastava,” A Framework for Dynamic Background Modeling and Shadow Suppression for Moving Object Segmentation in Complex Wavelet Domain”, Journal of Electronic Imaging, SPIE, 24(5) 051005 doi: 10.1117/1.JEI.24.5.051005. (SCI Impact Factor: 0.84).
  • Alok K. Singh Kushwaha, Rajeev Srivastava, "Multiview human activity recognition system based on spatio-temporal template for a video surveillance system," Journal of Electronic Imaging, SPIE, 24(5), 051004 (2015). doi: 10.1117/1.JEI.24.5.051004 (SCI Impact Factor: 0.84)
  • Tanima Dutta and Hari Prabhat Gupta, "Leveraging Smart Devices for Automatic Mood-transferring in Real-time Oil Painting",  IEEE Transactions on Industrial Electronics,  2016  (Accepted as a regular paper)  [Impact Factor 6.383].
  • Tanima Dutta and Hari Prabhat Gupta, "An Efficient Framework for Compressed Domain Watermarking in P-frames of HEVC- Encoded Video",  ACM Transactions on Multimedia Computing, Communications, and Applications (TOMM),  2016  (Accepted as a regular paper)  [Impact Factor 2.28].
  • Tanima Dutta and Hari Prabhat Gupta "A Robust Watermarking Framework for High Efficiency Video Coding (HEVC)- Encoded Compressed Video", Elsevier Journal of Visual Communication and Image Representation, volume 38, pp. 29-44, 2016 [Impact factor 1.361]. 
  • Pratik Chattopadhyay, Shamik Sural, and Jayanta Mukherjee, Frontal Gait Recognition from Occluded Scenes, Elsevier Pattern Recognition Letters, 63(1): 9-15, 2015.  
  • Pratik Chattopadhyay, Shamik Sural, and Jayanta Mukherjee, Information Fusion from Multiple Cameras for Gait-based Re-identification and Recognition, IET Image Processing, 9(11): 969-976, 2015. 
  • Aditi Roy, Pratik Chattopadhyay, Shamik Sural, Jayanta Mukherjee and Gerhard Rigoll, Modeling, Synthesis and Characterization of Occlusion in Videos, IET Computer Vision, 9(6): 821-830, 2015. 
  • Debanjan Sadhya and Sanjay Kumar Singh, “Providing robust security measures to Bloom filter based biometric template protection schemes”, Computers & Security, Volume 67, Pages 59–72, June 2017.
  • Santosh Kumar and Sanjay Kumar Singh, “Visual Animal Biometrics: Survey”, IET Biometrics, Volume 6, Issue 3, p. 139 – 156, May 2017.
  • S Kumar, D Datta, Sanjay Kumar Singh and AK Sangaiah, “An intelligent decision computing paradigm for crowd monitoring in the smart city”, Journal of Parallel and Distributed Computing, March 2017..
  • Deepanwita Datta, Shubham Varma, Sanjay Kumar Singh, “Multimodal retrieval using mutual information based textual query reformulation”, Expert Systems with Applications, Volume 68, Pages 81–92, February 2017.
  • Durgesh Singh, Sanjay Kumar Singh, “Dct based efficient fragile watermarking scheme for image authentication and restoration”, Multimedia Tools and Applications, Volume 76, Issue 1, pp 953–977, January 2017.