A-trous wavelet transform-based hybrid image fusion for face recognition using region classifiers

摘要

This paper presents a new hybrid fusion framework based on thermal and visible face images. Fusion of information is done here in two phases, first at the pixel level and then at the decision level. For the pixel level fusion process, a-trous wavelet transform is applied on both the thermal and visible face images. In decision level fusion, 34 region classifiers, each concentrating on a specified region of the face image, are tested individually for their ability to identify a person from the face image. The region classifiers, which contribute significantly in recognizing the face image, are considered for decision level fusion using majority voting. All experiments have been conducted on the UGC-JU face database and IRIS benchmark face database. The maximum recognition rate is about 97.22% for both the databases whereas decisions of 17 region classifiers among 34 are considered. Experimental results and comparative study show that the proposed fusion method provides a framework for recognition of face images in uncontrolled environments such as variations in illumination conditions, pose, and facial expressions.