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This thesis mainly study the problem of the accuracy and optimization of the feature extraction on the points of interest in images. Due to the complexity of the image and the interference of noise in the image, the traditional feature extraction algorithm based on the points of interest is difficult to extract the information which users interested in. In order to solve the above problems, an improved...
Shape analysis is an active and important branch in computer vision research field. In recent years, many geometrical, topological, and statistical features have been proposed and widely used for shape-related applications. In this paper, based on the properties of Distance Transform, we present a new shape feature, weight of boundary point. By computing the shortest distances between boundary points...
This paper presents a method for extracting texture and color hybrid features and constructing an adaptive weight operator, which can be used for content-based image retrieval (CBIR). This method extracts texture feature effectively based on Brushlet transform, quantifies in the HSV space, and extracts color feature by color histogram. K-mean clustering is introduced to count overall characteristics...
Based on Gabor wavelets, a novel multi-scale principal component analysis and support vector machine algorithm (MsPCA-SVM) for face recognition is proposed in this paper. Firstly, the Gabor wavelets transformation results including five scales and eight directions are calculated and 40 feature matrices which are reconstructed with the same scale and the same direction transform results of the different...
Extracting effective and reliable features is fundamental and critical for constructing target recognition systems. Flexible Feature Processing Mechanism emphasizes the integration of feature extraction arithmetic and the self-adaptation of feature selection. On one hand, it would try to dig up the valuable information on as many as possible aspects, so as to construct the feature extraction method...
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