Description: 计算欧几里德距离C语言源代码,次源码经测试可有效运行,源码简单易懂-Calculation of Euclidean distance C-language source code, sub-source has been tested and can be effectively run, easy-to-read source Platform: |
Size: 1024 |
Author:angel |
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: 產生k個d維的常態分布樣本，產生某個事前機率為P(wi)的常態分布的discriminant
function，計算任兩點間的Euclidean distance及Mahalanobis distance
-Generated k-d-dimensional normal distribution of samples to generate a prior probability P (wi) of the normal distribution of the discriminant function, calculated between any two points in Euclidean distance and Mahalanobis distance Platform: |
Size: 38912 |
Author:amy |
Hits:
Description: calculates the squared euclidean distance between all pairs of rows of two matrices. -calculates the squared euclidean distance between all pairs of rows of two matrices. Platform: |
Size: 1024 |
Author:qingpg518 |
Hits:
Description: 本文针对SLAM算法中数据关联过程，提出了一种简单易行的改进方法，将欧氏距离与马氏距离结合用于数据关联。算法不必计算地图所有特征与所有量测之间的马氏距离，而是首先利用相对简单的欧氏距离计算缩小了待关联特征的搜寻范围。利用人工合成数据的仿真结果表明，改进后的数据关联方法可以大幅减少系统计算量，提高关联效率，且不会造成错误关联的增加。-This article SLAM algorithm for data association process, a simple method to Euclidean distance combined with the Mahalanobis distance for data association. Algorithms do not have to calculate all the characteristics of the map with all measurements between the Mahalanobis distance, but the first to use a relatively simple calculation of Euclidean distance to be associated characteristics of narrowing the search. The use of synthetic data simulation results show that the improved methods of data association can significantly reduce the system to calculate the volume and improve the efficiency of association, and will not lead to errors associated with an increase. Platform: |
Size: 13312 |
Author:liancb |
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: 将图像提取gist向量，然后计算各向量之间的欧氏距离，进行比较。-Extracted gist vector image, and then calculate the Euclidean distance between vectors, for comparison. Platform: |
Size: 1024 |
Author:刘洋 |
Hits:
Description: Euclidean Distance Transform has been widely studied in computational geometry, image processing, computer graphics and pattern recognition. Euclidean distance has been computed through different algorithms like parallel, linear time algorithms etc. On the basis of efficiency, accuracy and numerical computations, existing and proposed techniques has been compared. This study proposed a new technique of finding Euclidian distance using sequential algorithm. An experimental evaluation has shown that proposed technique has reduced the drawbacks of existing techniques. And the use of sequential algorithm scans has reduced the computational cost. Platform: |
Size: 101376 |
Author:yasora |
Hits:
Description: Compute nearest neighbours (by Euclidean distance) to a set of points of interest from a set of candidate points.
The points of interest can be specified as either a matrix of points (as columns) or indices into the matrix of candidate points.
Points can be of any (within reason) dimension.
nearestneighbour can be used to search for k nearest neighbours, or neighbours within some distance (or both)
If only 1 neighbour is required for each point of interest, nearestneighbour tests to see whether it would be faster to construct the Delaunay Triangulation (delaunayn) and use dsearchn to lookup the neighbours, and if so, automatically computes the neighbours this way. This means the fastest neighbour lookup method is always used. Platform: |
Size: 30720 |
Author:nadir |
Hits:
Description: 计算两个矩阵之间的欧氏距离，对学生模式识别的人有帮助。-Calculated between the two Euclidean distance matrices, pattern recognition to students who have helped. Platform: |
Size: 1024 |
Author:袁冬 |
Hits:
Search - euclidean distance