Face and Gender Recognition Using Principal Component Analysis
Journal Title: International Journal on Computer Science and Engineering - Year 2010, Vol 2, Issue 4
Abstract
Face recognition is a biometric analysis tool that has enabled surveillance systems to detect humans and recognize humans without their co-operation. In this paper we evaluate the basics of the Principal Component Analysis (PCA) and verify the results of this algorithm on a training database of images. The same principle is in effect used to recognise the gender of the test image by evaluating the Euclidian distance of the test mage from the images in the database. The proposed gender and face recognition technique using PCA is verified for both est images of a man and a woman. It was observed that if the number of images of a particular subject was more in the atabase, the gender recognition becomes even better. The effect of salt and pepper noise and image cropping was also observed and the results hold true for noise up to 40 percent of the image pixels.
Authors and Affiliations
Dr. H. B. Kekre , Sudeep D. Thepade , Tejas Chopra
Keywords
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