Abstract
The face recognition system with large sets of training sets for personal identification normally attains good accuracy. In the project, we proposed algorithm for Feature Extraction based Face Recognition, Gender and Age Classification with only small training sets and it yields good results even with one image per person. This process involves three stages: Pre-processing, Feature Extraction and Classification. The geometric features of facial images like eyes, nose, mouth etc. are located by using Feature extraction algorithm and face recognition is performed. Based on the texture and shape information, gender and age classification is done by comparing histogram of the query image and the histogram of the images in dataset respectively. By using the proposed work , ratio of 100% for face matching, 90% for gender classification ,and 85% for age classification can be achieved .
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