Sudipta Banerjee


 

About me

     
  • Currently enrolled as PhD student in Computer Science and Engineering in Michigan State University
  • Primary adviser is Dr. Arun Ross, the director of iPRoBe lab 
  • Completed Masters in Engineering in Electronics and Telecommunication engineering from Jadavpur University, Kolkata, India in 2014
  • Completed Bachelors in Technology in Electronics and Communication Engineering from the West Bengal University of Technology, Kolkata, India in 2011

Contact Details:
428 S. Shaw Lane Rm. 3115 Michigan State University
East Lansing, MI 48824, United States
banerj24@cse.msu.edu     banerjeesudipta30@gmail.com

 

 

Research interests

 

Camera sensor identification for biometric images: Photo Response Non-Uniformity (PRNU) has been successfully utilized for sensor identification in the literature and is important in the context of image forensics. PRNU manifests as a consequence of artifacts associated with the sensor fabrication process. In iris biometrics, the images are captured using iris sensors typically operating in the near-infrared spectrum, which differ from conventional RGB sensors employed in the camera. Also, the iris images can be subjected to some pre-processing schemes, such as photometric modifications to aid in iris recognition. We evaluate different PRNU schemes in the context of iris sensor identification. We further analyze the impact of photometric transformations known to improve iris recognition performance on PRNU based sensor identification. In many image forensic applications, one can implicitly link the camera with the photographer. This raises privacy concerns, which can be mitigated via sensor de-identification. In this context, we deliberately perturb the image such that the PRNU based sensor classifier incorrectly assigns the modified image to a different sensor but without compromising the utility of the images. In our work, we aim to confound the iris sensor classifier, whilst preserving the iris recognition performance.


                                                                                                             


Deducing the structure of evolution between a set of photometrically transformed images: An image can undergo a sequence of photometric transformations such as, brightness and contrast adjustment to yield a set of near-duplicate images related to each other. Deduction of the hierarchical structure of evolution can be used for verifying the integrity of images. We develop a method which accepts as input a set of photometrically modified images, and estimate the pair-wise transformation parameters using a parameterized model. We further utilize the estimated parameters to obtain the relationship and depict it in the form of an Image Phylogeny Tree. The IPT is a directed acyclic graph which indicates the root node (original image) and the child nodes (transformed images) and how they are related to each other.


                                                                                 

Cyberattack pattern analysis : Defacement of webpages via insertion of graphics and text leads to denial of service attacks and causes financial setbacks to commercial websites. Cyberattacks can be malicious or inocuous depending on the intent of the attacker. Some attackers are repeat offenders who target specific websites or they have a common point of origin. In this work, we try to detect any discernible pattern in the cyberattacks which can help thwart such attacks in the future.

 

Publications

 

· S. Banerjee and A. Ross, " Face Phylogeny Tree: Deducing Relationships Between Near-Duplicate Face Images Using Legendre Polynomials and Radial Basis Functions," 10th IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS), Florida, 2019.

· S. Banerjee and A. Ross, " Smartphone Camera De-identification while Preserving Biometric Utility," 10th IEEE International Conference on Biometrics: Theory, Applications and Systems (BTAS), Florida, 2019.

· S. Banerjee, T. Swearingen, R. Shillair, J. Bauer, T. Holt and A. Ross, "Analysis of Cyberattack Patterns Across Longitudianl Data", 2nd Annual Conference on the Human factor in Cybercrime, Amsterdam, 2019. (Abstract accepted)

· S. Banerjee, V. Mirjalili and A. Ross, " Spoofing PRNU patterns of Iris Sensors while Preserving Iris Recognition," 5th International Conference on Identity, Security and Behavior Analysis (ISBA), Hyderabad, 2019. (Best paper award) URL: link to paper

· S. Banerjee and A. Ross, " Impact of Photometric Transformations on PRNU Estimation Schemes: A Case Study Using Near Infrared Ocular Images," 6th International Workshop on Biometrics and Forensics (IWBF), Sassari, 2018. (Best student paper award) URL: link to paper

· S. Banerjee and A. Ross, "Computing an image Phylogeny Tree from photometrically modified iris images,"IEEE International Joint Conference on Biometrics (IJCB), Denver, CO, 2017, pp. 618-626.doi: 10.1109/BTAS.2017.8272749. URL: link to paper

· S. Banerjee and A. Ross, "From image to sensor: Comparative evaluation of multiple PRNU estimation schemes for identifying sensors from NIR iris images," 5th International Workshop on Biometrics and Forensics (IWBF), Coventry, 2017, pp. 1-6.doi:10.1109/IWBF.2017.7935081. URL: link to paper

· V. N. Gangapure, S. Banerjee and A. S. Chowdhury, “Steerable local frequency based multispectral multifocus image fusion”, Information Fusion, Volume 23, 2015 Pages 99-115, ISSN 1566-2535 URL: link to paper

· S. Banerjee, V. N. Gangapure and A. S. Chowdhury, “Multispectral Multifocus Image Fusion with Guided Steerable Frequency and Improved Saliency”, In Proceedings of the Indian Conference on Computer Vision Graphics and Image Processing (ICVGIP '14). ACM, New York, NY, USA, Article 9, 8 pages. URL: link to paper

   

Curriculum vitae

Resume available here.