Face Detection Using an Adaptive Skin-Color Filter and FMM Neural Networks

In this paper, we present a real-time face detection method based on hybrid neural networks. We propose a modified version of fuzzy min-max (FMM) neural network for feature analysis and face classification. A relevance factor between features and pattern classes is defined to analyze the saliency of features. The measure can be utilized for the feature selection to construct an adaptive skin-color filter. The feature extraction module employs a convolutional neural network (CNN) with a Gabor transform layer to extract successively larger features in a hierarchical set of layers. In this paper we first describe the behavior of the proposed FMM model, and then introduce the feature analysis technique for skin-color filter and pattern classifier.