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The Research on Algorithms for Recognition of Cow Image Based on Wavelet Moment

Author: JinYiChu
Tutor: MaYan
School: Shanghai Normal University
Course: Applied Computer Technology
Keywords: Cows recognition Homomorphic filtering Regional Growth Eight-connected component labeling Wavelet Moment
CLC: TP391.41
Type: Master's thesis
Year: 2011
Downloads: 17
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Abstract


The cows identification is an important part of the management of the cows , and the previous identify cows mainly rely on manual identification , mainly uses electronic tags to identify cows picture , and use the computer to identify cows management is a new field . Cows image recognition is divided into three steps : to remove the impact of light , image segmentation and object recognition . In this paper, based on the homomorphic filtering processing algorithms wavelet transform and region growing algorithm based on the sub-block in the YCbCr color space , while eight neighborhood marking algorithm improvements . This paper completed the following work : (a) to remove the impact of light on the image segmentation and recognition . The light shines in the cows body surface reflective , so that part of the area of the cow in the picture , whose colors and the color is not the same as the original . In this paper, the YCbCr color space the homomorphic filtering processing algorithm based on wavelet transform . The image is first converted to the YCbCr color space, the luminance component using wavelet decomposition to filter unnecessary detail and with homomorphic filter removing light . (B ) In order to improve recognition speed , region growing algorithm based on sub-block - based region growing algorithm . 4 × 4 sub-block as a unit, as a sub-block is characterized first block inside color clustering and extract its color and texture features , and then according to the criteria subblock region growing . After the initial segmentation , this paper Finally, we propose an improved eight - neighborhood labeling algorithm to repair cracks and small holes within the target segmentation segmentation algorithm based on Otsu multi- threshold separating the target from the background . ( C) split the image to select the area of ??the largest black markings as target identification . First goal such as pan and zoom normalization process , followed with a three-dimensional B - spline function wavelet moment , and finally calculate the wavelet moment extracted eigenvalues ??with the eigenvalues ??of the cows in the database to compare obtained recognition results . Experiments show that the recognition algorithm proposed in this paper can effectively identify cows , the identification rate of about 84% .

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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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