H. R. Chennamma

Work place: Department of Computer Applications, JSS Science and Technology University, Mysuru, Karnataka, India

E-mail: hrchennamma@sjce.ac.in


Research Interests: Computer systems and computational processes, Pattern Recognition, Computer Architecture and Organization, Image Compression, Image Manipulation, Image Processing, Speech Recognition


Dr. Chennamma received her graduate degree in Computer Applications with distinction in the year 2003, Visvesvaraya Technological University, India and completed her Ph.D. in Computer Science from the University of Mysore in the area of Digital Image Forensics in 2011. Subsequently, she continued her Post Doctoral research in the Department of Computer Science and Engineering, University of North Texas, USA in 2012. Currently, she is an Associate Professor in the Department of Master of Computer Applications, JSS Science and Technology University, Mysuru, India. Previously, Chennamma served as a Senior Research Fellow (SRF) in National Computer Forensic Laboratory, Ministry of Home Affairs, Government of India, Hyderabad. She served as a Project Trainee for an year at the National Aerospace Laboratory (NAL), Bangalore and she also served as a software engineer for a year in a multinational software company, Bangalore. Chennamma is the recipient of two “Best Scientific Paper Awards” in the All India Forensic Science Conference, Kolkata, India in the year 2007 and another in National Cyber Safety and Security Standards Summit’17, Hyderabad, India. Her current research interests are Image Forensics, Pattern Recognition, Computer-Generated Image Forensics and Image Retrieval.

Author Articles
Image Hashing Through Spatio-triad Relationship

By Sowmya K. N. H. R. Chennamma

DOI: https://doi.org/10.5815/ijcnis.2022.05.05, Pub. Date: 8 Oct. 2022

Authenticating the content of the digital image has profound influence in legal matters and in court rooms. Image forensics plays an important role towards it. Proposed approach helps to authenticate the original image by generating a content based image signature that is a unique fingerprint for the image. Our novel approach establishes spatio triad relationship among features and finds the centre of gravity or centroid of the same after indexing. Topology of the triad relationship for the content based low level feature descriptors is preserved through aggregation until single key feature is deduced which is a 128 bit signature hash value and represented in decimal form. Density of feature keypoints influences the centre of gravity which acts as a unique signature for the given image. Manipulated image cannot contribute to restore / regenerate the same signature. We have verified our authentication approach for standard benchmark image dataset like MICC-F220, Columbia Image Splicing Evaluation dataset and Image manipulation dataset from Friedrich Alexander University and have found satisfactory results for the same. Content based image signature obtained is used to verify authenticity of image and for retrieval of video from database. Content based image fingerprint generated can also be considered for embedding as a watermark.

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