NDLI: Holistic and partial face recognition in the MWIR Band using manual and automatic detection of face-based features

Content Provider	IEEE Xplore Digital Library
Author	Osia, N. Bourlai, T.
Copyright Year	2012
Description	Author affiliation: West Virginia University, PO Box 6201, Morgantown, 26506, USA (Osia, N.; Bourlai, T.)
Abstract	Most of the benchmark face recognition (FR) approaches are designed to depend upon the usage of holistic or texture-based features of the human face. Here we present a new approach to the problem of middle-wave infrared (MWIR) facial recognition that realizes the full potential of the MWIR band. It consists, first, of a fully automated standardization of MWIR images prior to feature extraction through: skin segmentation, eye detection, inter-ocular and geometric normalization of our entire face dataset. Then, a statistically-based physiological feature extraction algorithm is used that is tailored to MWIR phenomenology: infrared-based features are extracted that consist of wrinkles, veins, edges, and perimeters of facial characteristics using anisotropic diffusion and top hat segmentation. At the next step, fiducial points are detected either manually, or automatically using different detectors such as a fingerprint-based minutiae detector, the Scale-Invariant Feature Transform (SIFT) detector, and the Speeded Up Robust Feature (SURF) detector. Finally, face matching is performed, utilizing fiducial points originally detected: end points and branch points on the face are filtered using the maximum pixel distance allowed between two matching points. Matching experiments are performed by using either the whole or sub-regions of the human face. Facial matching results on holistic faces emphasize the importance of data pre-processing as we achieve a rank-1 accuracy of at least 95%, independent of the fiducial point extraction method employed.
Starting Page	273
Ending Page	279
File Size	971428
Page Count	7
File Format	PDF
ISBN	9781467327084
e-ISBN	9781467327091
DOI	10.1109/THS.2012.6459861
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-11-13
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Image segmentation Image edge detection Face recognition Detectors Feature extraction Skin Face
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
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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9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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