A novel mechanism for dynamic multifarious and disturbed human face recognition using Advanced Stance Coalition (ASC). (September 2020)

• Record Type: Journal Article
• Authors: Munnangi, Ashok kumar; Rajeyyagari, Sivaram
• Is Part Of: Computers & electrical engineering. Volume 86(2020)
• Publication Date: 2020-09
• Subjects: Human Face recognition -- Image noise -- Advanced Stance Coalition -- Multifarious face recognition -- Naive Bayes -- Median filtering; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2020.106820
• Languages: English
• ISSNs: 0045-7906

Abstract

ABSTRACT: Multifarious face recognition is a technique of identifying or verifying the identity of an individual using several significant features of the face. Many of the existing algorithms use least significant features and hence provide lesser amount of accuracy. In this paper, a novel scheme named Advanced Stance Coalition (ASC) is proposed to classify faces even in the most challenging picture frames. In addition to providing maximum accuracy, the ASC algorithm also reduces the calculation time. The images are feature enhanced by employing median filtering scheme followed by MD5 hashing scheme to preserve its originality. The block dioptry distribution along with naive Bayes is used for feature classification. AR, Yale, and ORL databases are used to test the efficiency of the proposed scheme. From the results, it can be seen that the proposed scheme is more efficient even with noisy images.