Face detection using fuzzy granulation and Genetic algorithm in color images

Face Detection in images with complex background is a difficult and challenging problem. It can be considered as a classification problem in the sense that a given image region can be classified as face or non-face classes. In this paper, we propose a method based on skin color segmentation and clas...

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Hauptverfasser: Shemshaki, M., Amjadifard, R.
Format: Tagungsbericht
Sprache:eng
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Zusammenfassung:Face Detection in images with complex background is a difficult and challenging problem. It can be considered as a classification problem in the sense that a given image region can be classified as face or non-face classes. In this paper, we propose a method based on skin color segmentation and classification with fuzzy information granulation (FIG) for robust and fast face detection in color images. The proposed FIG-classifier constructs fuzzy granules based on pixels of image train data and classifies image regions using these fuzzy granules. We use Genetic algorithm to select representative features to generate the FIG-Classifier. Face detection task is performed based on classification of normalized skin color segments using the proposed classifier. Experimental results show effectiveness of the proposed method in comparison with the previous methods.
DOI:10.1109/ICARA.2011.6144889