Color Face Detection Based on PCNN Time Signature(<Special Issue>SOFT COMPUTING METHODOLOGIES AND ITS APPLICATIONS)

概要

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In this paper, a novel method is proposed to detect faces based on unit-linking PCNN time signature and skin color segmentation, in which no training is needed. A test image is first divided into overlapped blocks and extracted PCNN time signature as the detection features, which a two-dimensional image is projected to a one-dimensional feature space. The test blocks are matched to a face template based on Euclidean distance threshold and Skin color segmentation is used to reduce the search areas and to speed up the detection procedure. The candidate face blocks are clustered to determine the face number included in a test image and the size of the face areas. The method demonstrates successful face detection over a wide range of facial variations in scale, resolution, facial expressions, in the presence of various illumina-tion conditions and under complex background from outdoor photo collections. The simulation result proves that the method is translation, rotation and scale invariant and is insensitive to facial changes.
バイオメディカル・ファジィ・システム学会の論文