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The Main Technology Research about Human Face Detection and Recognition

Author: LiuQingShun
Tutor: LiuZhiJing
School: Xi'an University of Electronic Science and Technology
Course: Applied Computer Technology
Keywords: Skin color model Face Detection Face Recognition The discrete I spin transform Hidden Markov
CLC: TP391.41
Type: Master's thesis
Year: 2008
Downloads: 150
Quote: 1
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Face detection and recognition technology is one of the most active research topic in recent years, image processing, pattern recognition, artificial intelligence and other fields, it has a wide range of applications and important theoretical research value. Biometric face recognition and fingerprint, iris, compared with a direct, friendly, and convenient features is easy to be accepted by users. Face detection and recognition technology as an important element in the human-computer interaction, has great theoretical significance and application value. Human face detection method based on skin color information and the face recognition algorithm based on two-dimensional hidden Markov model and in-depth study, and developed face detection and recognition system usage, performance analysis, as well as specific applications do introduced. The main results of the work include the following aspects: 1) the frontal face detection and localization method. In this paper, a combination of skin color detection and spatial location of the facial features verification method. First of all, for the distribution and characteristics of skin color in the color space research, select a large number of color samples, the skin model in the specific color space through experiments. Thus face image skin color segmentation, to further detect facial features on the segmentation results. Then in accordance with the spatial positional relationship between the characteristics of the candidate face region feature verification, to determine whether the candidate face region is human face region. And mechanisms to reduce the number of candidate face region, combined with the Euler number. Experiments show that the method is feasible, and greatly improve the success rate of detection. 2) of the detected face region face recognition based on DCT coefficients Hidden Markov. Dimensional discrete I spin transform on the original image, most of the the energy of the original image are concentrated in the low-frequency component of the transform coefficients. These low frequency components are large amplitude, can be used to reconstruct an image. Retention of a small number of discrete cosine transform low-frequency component, while discarding the majority of the high frequency component, using the inverse transform similar restored image with the original image can be obtained, a new image and the original image there is a certain error, but the important information is preserved. Firstly, a discrete cosine transform on the image, determined coefficient vectors as training observation vector sequence of the hidden Markov model, and the optimization of the model parameters for face recognition. The experiment proved that this method has a high recognition rate, and good development prospects. 3) extensive testing experimental prototype face detection and recognition system implemented in this article. The results show that the system in the face detection and recognition of lighting conditions, changes in the expression of change in the attitude of the person face strong adaptability in a variety of complex conditions to maintain high detection and recognition rate, and at the same time achieve a high recognition speed.

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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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