Integarted Minimum Cost Sub-Block Matching Distance based Face Recognition using Internet of Things
Ch. Rathna Jyothi

Ch.Rathna Jyothi Asst. Professor, CSE Department, Prasad V Poturi Siddhartha Institute of Technology Kanuru, Vijayawada-7, India
Manuscript received on 21 August 2019. | Revised Manuscript received on 22 September 2019. | Manuscript published on 30 September 2019. | PP: 117-122 | Volume-8 Issue-11, September 2019. | Retrieval Number: J99940881019/2019©BEIESP | DOI: 10.35940/ijitee.J9994.0981119
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

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.
Keywords: Facerecognition, Occlusion, Fuzzy Segmentation, SVM
Scope of the Article: