Study On Illumination Preprocessing Approaches In Face Images

As one of the most successful branches of personal identification, face recognition has great potential applications in public safely, visual surveillance, digital identity certification, e-commerce, multimedia and digital entertainment and other fields. The face recognition technology has developed rapidly over the past 40 years, basically accurate identification of a specific environment, and has been found in some excellent commercial recognition software. While the face recognition algorithm performance degrades under uncontrolled environment such as variant illumination, head poses, facial expressions, occlusion on face and so on. Research indicates that, in face recognition, variations caused by illumination are more significant than the inherent differences between individuals. Therefore, how to effectively correct the illumination face images to achieve the pre-independent effect of light is an important topic in Face Recognition.In our study paper, the main work can be summarized as follows:(1) Studies the illumination preprocessing algorithm based on Retinex theory, improve the algorithm as:to remove the effect of illumination on human face images, enhancing the high-frequency of the image using wavelet transform before the implementation of the log-domain high-pass filter with the image.(2) In order to improve recognition rate of face image preprocess, combining three preprocessing algorithms with:improved light compensation algorithm based on Retinex theory, histogram equalization and gray-scale transformation of gamma, find an optimal combination.(3) Identify the pre-processing results of illumination compensation algorithm with PCA, LDA recognition algorithm, using the Yale B face database. Combine the characteristics of illumination compensation algorithm to analyze the results of the identification, Comparative of two identification methods with identification time, recognition rate.The results showed that the five light preprocessing algorithm design in the test, achieve better recognition rate when light environment is not ideal; in normal lighting circumstances, the preprocessing algorithm does not cause the deterioration of image quality. Which equalization and improved illumination compensation algorithm sub-step processing is best handled by the pretreatment. Histogram equalization, balanced on the role of gray scale, weakening the halo effect caused by homomorphic filtering, and homomorphic filtering filters the low frequency components of image, eliminate the image differences caused by illumination change.