Abstract
Face recognition includes analysis of an image and extracting its facial features will help to differentiate it from others. Scale Invariant Free Transform Features (SIFT) is one such algorithm used to differentiate effectively. The features extracted are invariant to rotation, image scale and illumination. In this paper, this algorithm has been experimented on both real time images capturing using web camera and standard YALE face database. While testing on real time images, the system proved to be efficient but exceptions were made in some situations like poor lighting conditions. Since the camera used was basic VGA (Video Graphics Array), the recognition was not very accurate. But SIFT provides efficient face recognition technique under pose, expression and varying illumination condition for the Yale database images.
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