Investigating Image Processing Techniques on Using Face Recognition
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 5
Abstract
Algorithms based on Principal Component Analysis (PCA) and subspace Linear Discriminate Analysis (LDA) are popular in face recognition. PCA is used to perform dimension reduction on human face data and LDA creates another subspace to improve discriminate of PCA features. BPNN is used for training and learning, leading to efficient and robust face recognition. This system consists of three basic parts, first: the Face Detection part- automatically detect human face image using BPNN, second: the various facial features extraction, and the third: face recognition are performed based on Principal Component Analysis (PCA) with BPNN. The dimensionality of face image is reduced by the PCA and the recognition is done by the BPNN for efficient and robust face recognition. This paper focuses on highlighting the strengths and limitations of the earlier proposed classification techniques. The paper provides an insight into the reviewed literature to reveal new aspects of research.
Authors and Affiliations
Khusbu Rani, Mr. Sukhbir Kamboj
Keywords
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