Description: 基于内容的图像检索示例代码，给定一幅原图像，在图像数据库中根据与原图像之间相似度的大小，搜索与原图像最接近的若干幅图像。本程序相似度主要以两幅图像之间直方图的距离为衡量标准，对此内容感兴趣的同学可以在此基础上加入更多的相似度判别算法。-Content-Based Image Retrieval sample code, given a piece of the original image, the image database in accordance with the similarity between the original image size, image search and the original number of the nearest images. This procedure mainly on the similarity between two images, the distance histogram for the measure, this content of interest to students on the basis of similarity to include more discriminant algorithm. Platform: |
Size: 43008 |
Author:张柳新 |
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Description: 一种基于方向信息的鲁棒型Hausdorff距离匹配方法。该方法采用方向信息提取图
像边缘,通过计算边缘匹配率( edge matching rate, EMR)获得候选匹配区域,然后采用修正后的Hausdorff距离构造
相似性测度。实验结果表明,该方法加快了匹配过程,提高了抗噪性能,并能够准确匹配含有遮挡和伪边缘点的图
像,从而解决了基于传统Hausdorff距离匹配方法因噪声点、伪边缘点和出格点而造成的误匹配问题。-Based on the direction of information Robust Hausdorff distance matching method. Methods The direction of the image edge information extraction, matching the rate by calculating the edge (edge matching rate, EMR) access to the candidate matching area, and then adopt a revised structure Hausdorff distance similarity measure. Experimental results show that the method to accelerate the matching process and enhance the anti-noise performance and the ability to accurately match the containing block and pseudo-edge image, so as to solve the Hausdorff distance based on the traditional matching method because of the noise, the pseudo-edge point and the far point matching problem caused by misuse. Platform: |
Size: 1140736 |
Author:南飞燕 |
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Description: 基于奇异值分解的人脸识别方法
梁毅雄 龚卫国 潘英俊 李伟红 刘嘉敏 张红梅
提出了一种将傅里叶变换和奇异值分解相结合的人脸自动识别方法.首先对人脸图像进行傅里叶变换,得到其具有位移不变特性的振幅谱表征.其次,从所有训练图像样本的振幅谱表征中给定标准脸并对其进行奇异值分解,求出标准特征矩阵,再将人脸的振幅谱表征投影到标准特征矩阵后得到的投影系数作为该人脸的模式特征.然后,对经典的最近邻分类器算法进行了改进,并采用模式特征之间的欧式距离作为相似性度量,从而完成对未知人脸的识别.采用ORL (Olivetti Research Laboratory)人脸库对本文提出的人脸识别方法进行验证,获得了100.00 的识别率.实验结果表明,本方法优于现有的基于奇异值分解的人脸识别方法,且对表情、姿态变换等具有一定的鲁棒性.
-Face recognition based on singular value decomposition method
Deliberate simultaneously Gong Weiguo Li Wei Hung Stephen Lau, Hong-Mei Zhang Ying-Jun Pan
Paper, a Fourier transform and singular value decomposition of the combination of automatic face recognition. First of all, the face image by Fourier transformation, it has the same characteristics of the displacement amplitude spectra. Secondly, all training The amplitude spectrum of the sample images given in standard face representation and its singular value decomposition, find the standard characteristic matrix, then the amplitude of spectral characterization of human faces projected onto the standard characteristic matrix of projection coefficients obtained as the face of the model features . Then, the classical nearest neighbor classifier is improved, and the use of Euclidean distance between pattern features as the similarity measure, thus completing the identification of unknown human faces. using ORL (Olivetti Research La Platform: |
Size: 58368 |
Author:houhj |
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Description: 学术论文，介绍了一种采用方向信息提取图
像边缘,然后采用修正后的Hausdorff距离构造
相似性测度进行图像匹配的方法。-Papers, a direction information image edge extraction, and then using the Hausdorff distance in the revised construct a similarity measure for image matching method. Platform: |
Size: 1148928 |
Author:刘伟豪 |
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Description: we present an improved fuzzy
C-means (FCM) algorithm for image segmentation by introducing
a tradeoff weighted fuzzy factor and a kernel metric. The
tradeoff weighted fuzzy factor depends on the space distance of
all neighboring pixels and their gray-level difference simultaneously.
By using this factor, the new algorithm can accurately
estimate the damping extent of neighboring pixels. In order to
further enhance its robustness to noise and outliers, we introduce
a kernel distance measure to its objective function. The new
algorithm adaptively determines the kernel parameter by using
a fast bandwidth selection rule based on the distance variance
of all data points in the collection. Furthermore, the tradeoff
weighted fuzzy factor and the kernel distance measure are both
parameter free. Experimental results on synthetic and real images
show that the new algorithm is effective and efficient, and is
relatively independent of this type of noise. Platform: |
Size: 1024 |
Author:李蕾 |
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Description: 提出一种基于DP匹配的特征矩阵相似性度量方法。首先,在对象矩阵与样本矩阵的行向量之间采用一维DP匹配方法,产生一个相似行向量来替代对象矩阵。然后再用一维DP匹配计算相似行向量与样本矩阵的标准行向量之间的匹配距离。最后在匹配距离上定义两个特征矩阵的相似度。此方法本质上是将二维特征矩阵的匹配问题转化为两个一维向量的DP匹配,适用于解决二维对象的识别和检索问题。在图像检索系统平台中对本文给出的相似性度量方法进行验证,结果表明此方法是有效的。-DP matching is proposed based on the characteristic matrix similarity measure. First, the line between the matrix and vector objects sample matrix using a one-dimensional DP matching method produces a similar row vector matrix instead of the object. Then use the one-dimensional DP matching distance calculation similar matches row vector of the sample standard matrix row vectors. The last two features define the similarity matrix in the matching distance. The matching problem is a two-dimensional matrix conversion feature of this method is essentially a two-dimensional vector of DP matching, suitable for solving the problem identification and retri of two-dimensional objects. Similarity measurement in image retri system platform for this paper to verify the results show that this method is effective. Platform: |
Size: 496640 |
Author:fangsm |
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Description: 基于马氏距离度量的局部线性嵌入算法
局部线性嵌入算法(LLE)中常用欧氏距离度量样本间相似度.而 对于图像等高维数据,欧氏距离不能准确体现样本间的相似程度.文中提出基于马氏距离度量的局部线性嵌入算法(MLLE).算法首先从现有样本中学习到一个 马氏度量,然后在LLE算法的近邻选择、现有样本及新样本降维过程中用马氏度量作为相似性度量.将MLLE算法及其它典型的流形学习算法在ORL和 USPS数据库上进行对比实验,结果表明MLLE算法具有良好的识别性能.
-Based on local linear embedding algorithm Mahalanobis distance metric LLE algorithm (LLE) common Euclidean distance measure of similarity between the samples. For high-dimensional image data, Euclidean distance can not accurately reflect the degree of similarity between samples. In this paper, Mahalanobis distance metric based on local linear embedding algorithm (MLLE). Firstly, learning the existing sample to a Markov measure, then LLE neighbor algorithm selection, existing samples and new samples dimensionality reduction process using Markov measure as a similarity measure would MLLE algorithms and other typical manifold learning algorithm on ORL and USPS to compare experimental results show MLLE algorithm has good recognition performance. Platform: |
Size: 406528 |
Author:fangsm |
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Description: 得到图像的特征点以及对应的特
征向量后，采用关键点特征向量的欧式距离作为两幅图
像中关键点的相似性判定度量(The feature points and corresponding features of the image are obtained
After the eigenvector, the Euclidean distance of the feature vector of the key points is used as the two map
Similarity measure of key points in image) Platform: |
Size: 1209344 |
Author:四六年纪源
|
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Description: 载入任意图像，在图像上自由选取任意两点，自动测量图像的像素距离（pixel）和进行实际距离（mm）的转换程序，C#写的，导入VS项目中直接运行可见效果。(Load any image, select any two points freely on the image, automatically measure the pixel distance of the image and carry out the conversion program of the actual distance , written by C# and directly run the visible effect in the imported vs project.) Platform: |
Size: 257024 |
Author:来一碗担担面 |
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Search - measure distance in image