Description: This function computes Euclidean distance transform for 3D binary image with non-trivial aspect ratio (i.e. anisotropic pixels). The algorithm uses fast optimized line-scans and is actually faster than MATLAB s BWDIST implementation of search on optimized kd-tree for many cases. It also uses cell-array representation for internal data, and thus is less demanding to physical memory. Platform: |
Size: 49720 |
Author:fangfei |
Hits:
Description: This function computes Euclidean distance transform for 3D binary image with non-trivial aspect ratio (i.e. anisotropic pixels). The algorithm uses fast optimized line-scans and is actually faster than MATLAB s BWDIST implementation of search on optimized kd-tree for many cases. It also uses cell-array representation for internal data, and thus is less demanding to physical memory. Platform: |
Size: 49152 |
Author:fangfei |
Hits:
Description: 计算2组象素的最小距离 minimum euclidean distance calculation between 2 groups pixels and returns the distance and pixel coordinations文件内容:test_min_distance5a.tif, CONTENTS.M, euclidean_distance.m, test_calculate_min_distance.m, test_min_distance1a.tif, test_min_distance1b.tif, test_min_distance2a.tif, test_min_distance2b.tif, test_min_distance3a.tif, test_min_distance3b.tif, test_min_distance4a.tif, test_min_distance4b.tif, calculate_min_distance.m, test_min_distance5b.tif-Group 2-pixel calculation of minimum distance between a minimum euclidean distance calculation between 2 groups pixels and returns the distance and pixel coordinations the content of the document: test_min_distance5a.tif, CONTENTS.M, euclidean_distance.m, test_calculate_min_distance.m, test_min_distance1a.tif, test_min_distance1b.tif, test_min_distance2a.tif, test_min_distance2b.tif, test_min_distance3a.tif, test_min_distance3b.tif, test_min_distance4a.tif, test_min_distance4b.tif, calculate_min_distance.m, test_min_distance5b.tif Platform: |
Size: 30720 |
Author:田卉 |
Hits:
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 |
Hits:
Description: SLIC主要运用K-means聚类算法进行超像素的处理，聚类算法中的距离度量不仅仅包括颜色空间的颜色距离还包括像素坐标的欧氏距离。所以K-means聚类的中心点由五维向量组成。其中包括，记录LAB颜色空间下的像素以及该像素点的XY坐标，由于XY坐标不能和颜色空间直接进行计算，所以添加了一个紧密度的参数。(slic superpixelSLIC mainly uses the K-means clustering algorithm for ultra pixel processing, the distance measurement in the clustering algorithm includes not only the color distance of the color space, but also the Euclidean distance of the pixel coordinates. Therefore, the central point of K-means clustering consists of five dimensional vectors. These include the recording of pixels in the LAB color space, and the XY coordinates of the pixel points, so that a parameter of compactness is added because the XY coordinates cannot be directly computed with the color space.) Platform: |
Size: 309248 |
Author:还有叫二哈的
|
Hits:
Description: (1) 读取图片 ，转换为灰度图像；
(2) 对 view1.png view1.png view1.png view1.png和 View5 .png .png 将图像 按照 4x4 像素 /方格 的形式 进行 分块；
(3) 考虑 边缘的相对稳定 性，以及 双目 成像 视差 规律 ，在第一幅图像分割得 到的块图像周围 20 个像素 个像素 的距离区间内由近到远进行搜索，寻找 与该块 欧氏距离最近的块作为新位置 ；
(4) 计算 视差 ，将每个小块 中代表点 的视差 信息转换到整个 区间 ；
(5) 将视差转 换为 深度，并归一化到 0-255 区间内 ，并显示图片 ；((1) read the picture and convert it to gray image.
(2) view1.png, view1.png view1.png view1.png and View5.Png.Png are partitioned according to 4x4 pixel / grid.
(3) considering the relative stability of the edge and the parallax rule of the binocular imaging, the nearest to the nearest block of the block's Euclidean distance is searched as a new position in the distance between the 20 pixels of the block image divided by the first image.
(4) calculate parallax and transform the parallax information of the representative points in each block to the whole interval.
(5) convert parallax to depth and normalize to 0-255 interval and display pictures.) Platform: |
Size: 8218624 |
Author:yangxm2011 |
Hits:
Search - euclidean distance of pixels