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Research on Fast Face Detection Algorithm Based on Skin Color Information

Author: WangLiJuan
Tutor: ZhouJiLiu；PangZuo
School: Sichuan University
Course: Software Engineering
Keywords: Face Detection Skin color model Color / grayscale images Skin color segmentation Region labeling algorithms
CLC: TP391.41
Type: Master's thesis
Year: 2004
Downloads: 965
Quote: 12
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Abstract


Automatic face recognition system is an important research topic in the field of computer vision, automatic face recognition system as locate the face of face detection is the basis of the normal face recognition system to work efficiently. Non-rigid face, people face detection is a fairly complex pattern recognition problem. In recent years, face detection in security monitoring, based on the potential application in the field of content-based image retrieval, face detection has become a separate issue. Universal attention by many researchers. Face detection method consists of the appearance-based methods, feature-based approach, based on template matching method based on skin color method. To use color information for face detection, intuitive, fast, simple to use it for automatic face recognition system face localization aspect is very applicable. The statistical model based on facial complexion, the skin color region segmentation algorithm in different color space. Institute relates to the color space comprises a YCbCr space, HSI space, KL skin color space, YUV space, YIQ space. The specific approach is the original color image is converted from RGB color space to the color space, select a large number of skin color samples in a specific color space by experimental skin model, find the skin color range. On the basis of skin color model, further study and more than two different applications (simple background single face detection in complex background face detection), the novelty of the real-time fast face detection based on skin color information The algorithm is different treatment depending on the application characteristics. Relatively simple background single face detection application of the projection method, the algorithm first to use color model for color image segmentation of skin color region and non-skin-color area, and then the skin tone area for horizontal and vertical projection, the projection results locate the face . More than face detection in complex background is mainly applied to the region labeling algorithms and face judgment based on knowledge rules, the algorithm still using skin color model for color image segmentation of skin color region and non-skin color region by region labeling algorithms classification different skin-color area, the face area of ??application for each skin color prior knowledge of rules to determine a candidate face region, then the candidate face region color Sichuan University engineering master's degree thesis based on skin color information fast face detection algorithm images into the gray-scale image of the luminance space, the comparison of the gray level distribution of the human face with the proposed rules for face authentication and locate the face, according to the result. Algorithm combination of color and grayscale space analysis, eliminating the complex background color and skin color similar to the distribution of gray space and face a big gap between the objects. And has a real-time rapid detection; limited advantages of scale-free, posture, facial expressions. Is this study many of the face detection method currently can not be achieved, with a high practical value and also has special significance for future research. The experimental results demonstrate the effectiveness of the proposed method, suitable for automatic face recognition system face detection link. Keywords: face detection skin color model Color / Grayscale image skin color segmentation algorithm of region labeling

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device
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