Abstract
PCA is utilized in the area of recognition of face, fingerprint, handprint, industrial robotics, and mobile robotics. In the face recognition, research shows that the success rate is not satisfactory for a variant of poses which have rotation gap of more than 30°. If there are lots of variations in lightning, expressions, and pose variation, then PCA results are not up to the mark in the existing algorithm. This problem is arising in mind. The objective of the present paper is to study and propose modified PCA and Eigen-face-based algorithm to improve result with the accuracy of face recognition. In this paper, we focus on the pose variations which have 30° range of pose in image.
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Declaration
The work reported in this chapter is approved by the ethical approval committee of School of Computational Science, SRTMU, Nanded (MS)-India. The committee consists of Dr. G. V. Chowdhary (Chairman), Dr. S. D. Khamitkar, Dr. H. S. Fadewar, Mr. M. D. Wangikar. Further, the subjects under test had given their written consent for the experiments and publication of this work.
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Tatepamulwar, C.B., Pawar, V.P., Khamitkar, S.D., Fadewar, H.S. (2019). Technique of Face Recognition Based on PCA with Eigen-Face Approach. In: Iyer, B., Nalbalwar, S., Pathak, N. (eds) Computing, Communication and Signal Processing . Advances in Intelligent Systems and Computing, vol 810. Springer, Singapore. https://doi.org/10.1007/978-981-13-1513-8_92
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DOI: https://doi.org/10.1007/978-981-13-1513-8_92
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