Background and activities
Raghavendra Ramachandra is working as a Professor in Department of Information Security and Communication Technology (IIK). He is member of Norwegian Biometrics Laboratory (http://nislab.no/biometrics_lab) at NTNU Gjøvik.
Background:
B.E (Electronics and Communication) from University of Mysore, India.
M.Tech (Digital Electronics and Advance Communication Systems) from Visvesvaraya Technological University, India.
Ph.D. (Computer Science with specialization of Pattern Recognition and Image Processing) from the University of Mysore, India and Telcom SudParis, Paris, France.
Research Interests
Pattern Recognition, Image and video analytics, Biometrics, Human Behaviour Anlaysis, Video Surviellance, Health Biometrics, Smartphone Authentication.
Scientific, academic and artistic work
A selection of recent journal publications, artistic productions, books, including book and report excerpts. See all publications in the database
Journal publications
- (2018) Improved ear verification after surgery - An approach based on collaborative representation of locally competitive features. Pattern Recognition. vol. 83.
- (2017) Multi-patch deep sparse histograms for iris recognition in visible spectrum using collaborative subspace for robust verification. Pattern Recognition Letters. vol. 91.
- (2017) A new multi-modal approach to bib number/text detection and recognition in Marathon images. Pattern Recognition. vol. 61.
- (2017) Biometric Symmetry: Implications on Template Protection. Proceedings of the European Signal Processing Conference.
- (2017) Multi-biometric template protection based on bloom filters. Information Fusion. vol. 42.
- (2017) Presentation Attack Detection Methods for Face Recognition Systems: A Comprehensive Survey. ACM Computing Surveys. vol. 50 (1).
- (2017) Collaborative representation of statistically independent filters? response: An application to face recognition under illicit drug abuse alterations. Lecture Notes in Computer Science. vol. 10270 LNCS.
- (2017) Face Presentation Attack Detection by Exploring Spectral Signatures. IEEE Computer Society Conference on Computer Vision and Pattern Recognition workshops. vol. 2017-July.
- (2017) Transferable Deep-CNN Features for Detecting Digital and Print-Scanned Morphed Face Images. IEEE Computer Society Conference on Computer Vision and Pattern Recognition workshops. vol. 2017-July.
- (2017) Biometric Systems under Morphing Attacks: Assessment of Morphing Techniques and Vulnerability Reporting. Lecture Notes in Informatics.
- (2017) Multi-biometric template protection on smartphones: An approach based on binarized statistical features and bloom filters. Lecture Notes in Computer Science. vol. 10125 LNCS.
- (2017) Fusing Biometric Scores Using Subjective Logic for Gait Recognition on Smartphone. Lecture Notes in Informatics.
- (2016) Cross-Eyed - Cross-Spectral Iris/Periocular Recognition Database and Competition. Lecture Notes in Informatics. vol. P-260.
- (2016) Learning deeply coupled autoencoders for smartphone based robust periocular verification. Proceedings of IEEE international conference on image processing. vol. 2016-August.
- (2015) Video Presentation Attack Detection in Visible Spectrum Iris Recognition Using Magnified Phase Information. IEEE Transactions on Information Forensics and Security. vol. 10 (10).
- (2015) Smartphone based visible iris recognition using deep sparse filtering. Pattern Recognition Letters. vol. 57.
- (2015) Exploring the Usefulness of Light Field Camera for Biometrics : An Empirical Study on Face and Iris Recognition. IEEE Transactions on Information Forensics and Security.
- (2015) Presentation Attack Detection for Face Recognition Using Light Field Camera. IEEE Transactions on Image Processing. vol. 24 (3).
- (2015) Robust Scheme for Iris Presentation Attack Detection Using Multiscale Binarized Statistical Image Features. IEEE Transactions on Information Forensics and Security. vol. 10 (3-4).
- (2015) Texture based features for robust palmprint recognition: a comparative study. EURASIP Journal on Information Security. vol. 5.