Integarted minimum cost sub-block matching distance based face recognition using internet of things

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Abstract

Abstract: 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.

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APA

Jyothi, C. R. (2019). Integarted minimum cost sub-block matching distance based face recognition using internet of things. International Journal of Innovative Technology and Exploring Engineering, 8(11), 117–122. https://doi.org/10.35940/ijitee.J9994.0981119

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