A New Era for Face Identifications System Using Fusion Method

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Volume 2, Issue 9 (September, 2016)
Publication No:
Bhagya Arora, Er. Sushil Kamboj
9 x

Face recognition from images is a sub-area of the general object recognition problem. Identifying an individual from his or her face is one of the most nonintrusive modalities in biometrics. It is of particular interest in a wide variety of applications. Although the current face recognition systems have achieved good results for face images that are taken in a controlled environment, they perform poorly in uncontrolled situations. It is possible that breakthrough solutions to tough computer vision problems may be found by looking beyond the visual modality. Face recognition has been a topic of active research since the 80‘s, proposing solutions to several practical problems. Face recognition is probably the biometric method easier to understand, because we identify people by mainly their faces. However the recognition process used by the human brain for identifying faces has not a concrete explanation. Because it is now essential to have a reliable security systems in offices, banks, businesses, shops, etc. several approaches have been developed, among them the face-based identity recognition or verification systems are a good alternative for the development of such security systems Olivares-Mercado et al. We have worked on both face recognition and detection techniques and developed algorithms for them. In face recognition, proposed Fusion Technique is applied on different type of facial images, these techniques works well under robust conditions like complex background, different face positions. These algorithms give different rates of recognition under different conditions as experimentally observed. In face detection, we have developed a hybrid fusion technique that can detect human faces from an image. It has been observed that the proposed method achieved the 94 % face recognition rate on different facial images which is far better than the existing techniques. We have simulated the algorithm in MATLAB successfully.

Gaussian model, Color space, Accuracy, True positive rate, false negative rate, Fusion method, Histogram, Face Detection