NDLI: Face sketch-photo recognition using local gradient checksum: LGCS

Content Provider	Springer Nature Link
Author	Roy, Hiranmoy Bhattacharjee, Debotosh
Copyright Year	2016
Abstract	A new approach for matching of face sketch images with face photo images and vice versa has been presented here. For the extraction of local edge features from both the sketch and photo images, a new local feature called local gradient checksum (LGCS) has been developed. LGCS is a modality reduction local edge feature on gradient domain. It is calculated as the summation of four pairs of gradient differences between two local pixels that are at 180° with each other. The Euclidean distance between query sketch and gallery of photos are measured depending on extracted LGCS features. To further improve the result, a multi-scale LGCS is proposed. A rank-1 accuracy of 100 % is achieved in a gallery of 606 photos consisting of CUHK, AR, and XM2VTS face dataset. The proposed face sketch-photo recognition system requires neither learning procedures nor training data. Further, the experiment is extended to test the robustness of the proposed algorithm on blurred, noisy and disguised sketches, as well as photos. Under those situations also, LGCS has outperformed center-symmetric local binary pattern, directional local extrema pattern and weber local descriptor feature extraction techniques.
Starting Page	1457
Ending Page	1469
Page Count	13
File Format	PDF
ISSN	18688071
Journal	International Journal of Machine Learning and Cybernetics
Volume Number	8
Issue Number	5
e-ISSN	1868808X
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2016-03-14
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Gradient-face Checksum LGCS MLGCS FSPR-system Computational Intelligence Artificial Intelligence (incl. Robotics) Control, Robotics, Mechatronics Complex Systems Systems Biology Pattern Recognition
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Vision and Pattern Recognition Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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