Abstract

Face recognition technology has rapidly evolved and become more popular in recent years. It is being used for both research and other applications such as security systems. One of the key challenges in face recognition systems is to identify the role of different cues for face identification. The role of color, which appears to be a salient attribute of faces, is debated within the literature. Some research has suggested that it confers little recognition advantage for identifying faces. Other research suggests that color is a very important cue in face identification. The clear perception of colors in the environment illustrates that color must be important in the interpretation of complex scenes and recognizing objects in the environment. In this thesis several face recognition methods are introduced. Experiments were conducted using both grayscale and color images. The accuracy of each algorithm has been identified and a comparison was performed between them in terms of recognition rates. A system is also proposed, which uses color features for face recognition. This system can be used by different face recognition algorithms. The goal of this study is to show the differences between some popular face recognition methods (new and traditional) and also the role of color in face recognition using different face recognition algorithms. The results of our experiments show that using color improves the recognition rate for traditional and new methods. The improvement is more obvious for traditional methods because the recognition rate is not near the peak