Abstract
It has become a necessity than a mere requirement in computer vision and image analysis technology over years, for image database identifications and identity verifications through iris scan, color, occlusions, texture of the face images. Also we could see security cameras installed under surveillance in sensitive areas such as Airports, Security on defense system, ATMs, in schools and colleges, banks, offices etc. In order to recognize the image of a person and identify, there are plethora of approaches. However, there are many problems which are still unsolved in the face recognition. This paper provides a till-date survey of the image face recognition showcasing the complete review of the research underwent on linear face recognition approaches and throw light upon certain non-linear approaches for the future case of study. The survey is made only with principal component analysis as the key on algorithms which are analyzed for its pros and cons in the purview of databases and classifiers. The survey shows the linear phase with least complex to the most complex issues with solutions and challenges faced by many authors.
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Belavadi, B., Mahendra Prashanth, K.V., Raghu, M.S., Poojashree, L.R. (2020). Subspace Based Face Recognition: A Literature Survey. In: Raj, J., Bashar, A., Ramson, S. (eds) Innovative Data Communication Technologies and Application. ICIDCA 2019. Lecture Notes on Data Engineering and Communications Technologies, vol 46. Springer, Cham. https://doi.org/10.1007/978-3-030-38040-3_33
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DOI: https://doi.org/10.1007/978-3-030-38040-3_33
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