NDLI: Segmentation of Different Skin Colors with Different Lighting Conditions by Combining Graph Cuts Algorithm with Probability Neural Network Classification, and its Application

Content Provider	Springer Nature Link
Author	Hwang, Chih Lyang Lu, Kai Di Pan, Yi Tsung
Copyright Year	2012
Abstract	It is realized that fixed thresholds mostly fail in two circumstances as they only search for a certain range of skin color: (i) any skin-like object may be classified as skin if skin-like colors belong to fixed threshold range; (ii) any true skin for different races may be mistakenly classified as non-skin if that skin colors do not belong to fixed threshold range. In this paper, graph cuts (GC) is first extended to skin color segmentation. Although its result is acceptable, a complex environment with skin-like objects or different skin colors or different lighting conditions often results in a partial success. It is also known that probability neural network (PNN) has the advantage of recognizing different skin colors in cluttered environments. Therefore, many images with skin-like objects or different skin colors or different lighting conditions are segmented by the proposed algorithm (i.e., the combination of GC algorithm and PNN classification with other functions, e.g., morphology filtering, labeling, area constraint). The compared results among GC algorithm, PNN classification, and the proposed algorithm are presented not only to verify the accurate segmentation of these images but also to reduce the computation time. Finally, the application to the classification of hand gestures in complex environment with different lighting conditions further confirms the effectiveness and efficiency of our method.
Starting Page	89
Ending Page	109
Page Count	21
File Format	PDF
ISSN	13704621
Journal	Neural Processing Letters
Volume Number	37
Issue Number	1
e-ISSN	1573773X
Language	English
Publisher	Springer US
Publisher Date	2012-12-29
Publisher Place	Boston
Access Restriction	Subscribed
Subject Keyword	Segmentation of skin colors Graph cuts Probability neural network Bayesian classifier Hand gestures Artificial Intelligence (incl. Robotics) Statistical Physics, Dynamical Systems and Complexity Computational Intelligence
Content Type	Text
Resource Type	Article
Subject	Neuroscience Artificial Intelligence Computer Networks and Communications Software

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
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in