Publisher : Korean Institute of Intelligent Systems
DOI : 10.5391/JKIIS.2016.26.2.120
Title & Authors
Design of RBFNNs Pattern Classifier Realized with the Aid of Face Features Detection Park, Chan-Jun; Kim, Sun-Hwan; Oh, Sung-Kwun; Kim, Jin-Yul;
In this study, we propose a method for effectively detecting and recognizing the face in image using RBFNNs pattern classifier and HCbCr-based skin color feature. Skin color detection is computationally rapid and is robust to pattern variation for face detection, however, the objects with similar colors can be mistakenly detected as face. Thus, in order to enhance the accuracy of the skin detection, we take into consideration the combination of the H and CbCr components jointly obtained from both HSI and YCbCr color space. Then, the exact location of the face is found from the candidate region of skin color by detecting the eyes through the Haar-like feature. Finally, the face recognition is performed by using the proposed FCM-based RBFNNs pattern classifier. We show the results as well as computer simulation experiments carried out by using the image database of Cambridge ICPR.
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