数字图像特征提取+matlab源代码
毕业论文关键词：图像预处理技术；LBP；CLBP；形状特征；矩特征
Abstract Image feature extraction technology is a concept of image processing, which can be performed by a computer for image feature extraction and analysis. Sometimes a certain point, a curve, the area in the image can be seen as a subset. According to different subsets, the methods of digital image extraction are different. Typical features include edge feature, characteristic shape, color, texture and other features. These features information plays an important role on the identification and classification of images. In practical problems, sample pictures mixing a lot of irrelevant information, image feature extraction may be subject to background illumination, size and other noise. Therefore, how to extract a good characterization of performance are subject to noise interference minimum characteristic parameter. In this paper, the selected sample images and experiments require gray-scale processing, and image smoothing. The paper mainly uses median filter and neighborhood average method for image preprocessing. On the basis of pre-processing, the paper is going to extract the feature of texture and shape about digital image. In the shape feature extraction, on the one hand, some of the basic parameters of the shape of sample images, including area, perimeter, circularity and shape complexity of comparing are measured; on the other hand, binding characteristics of moments and mean, variance, entropy, gradient analyzes the characteristics of the shape. In the texture feature extraction, using local binary patterns and completely local binary pattern to extract texture feature. Extracting Histogram of CLBP and LBP of sample images compares their similarity by computing histogram distance of the training image and test image. Equivalence mode selects LBP, LBP rotation invariant pattern, CLBP_S mode and CLBP_S_M four modes, using the nearest neighbor classifier to classify images.
Keywords: image processing; LBP; shape feature; moments feature
目录
第一章绪论.1
1.1研究意义..1
1.2图像特征提取技术的发展趋势2
1.3研究内容..2
1.4研究方法..2
第二章图像预处理技术.4
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