Open AccessIntegarted Minimum Cost Sub-Block Matching Distance based Face Recognition using Internet of Things
Author(s) -
Ch.Rathna Jyothi*
Publication year - 2019
Publication title -
international journal of innovative technology and exploring engineering
Language(s) - English
Resource type - Journals
ISSN - 2278-3075
DOI - 10.35940/ijitee.j9994.0981119
Subject(s) - facial recognition system , artificial intelligence , block (permutation group theory) , face (sociological concept) , computer science , computer vision , pattern recognition (psychology) , cluster analysis , matching (statistics) , three dimensional face recognition , face detection , mathematics , statistics , social science , geometry , sociology
Now a days one of the critical factors that affects the recognition performance of any face recognition system is partial occlusion. The paper addresses face recognition in the presence of sunglasses and scarf occlusion. The face recognition approach that we proposed, detects the face region that is not occluded and then uses this region to obtain the face recognition. To segment the occluded and non-occluded parts, adaptive Fuzzy C-Means Clustering is used and for recognition Minimum Cost Sub-Block Matching Distance(MCSBMD) are used. The input face image is divided in to number of sub blocks and each block is checked if occlusion present or not and only from non-occluded blocks MWLBP features are extracted and are used for classification. Experiment results shows our method is giving promising results when compared to the other conventional techniques.