A novel mechanism for dynamic multifarious and disturbed human face recognition using advanced stance coalition (ASC). (June 2020)

• Record Type: Journal Article
• Authors: Kumar, M. Ashok; Rajeyyagari, Sivaram
• Is Part Of: Computers & electrical engineering. Volume 84(2020)
• Publication Date: 2020-06
• 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.2020.106642
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Multifarious face recognition is a significant and challenging issue in human face recognition area. All those existing mechanisms for this issue has the least significant features with less expected outcome in the present technical scenario. In this paper, a novel scheme named Advanced Stance coalition to recognize human faces in the frame is propounded. The significant feature in ASC is to reduce the calculation time and to improve the result accuracy. Initially, images collected undergo feature extraction to identify the human face. Then, the median filtering is applied to remove noise and extract its feature. In the output section, MD5 hashing scheme is employed to prevent originality using block dioptry distribution with naive Bayes. The propounded ASC has significant features and suggests many details at training period which offers better results in the examination phase. From the result, it's clear that the proposed scheme is more persistent to noise and other major disturbances.