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基于小波变换的图像拼接,用到SIFT特征点匹配,内容包括源代码及待匹配图像-Image Stitching Based on Wavelet Transform, SIFT feature points used in matching
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采用sift算法获取图像之间的匹配点,并用rance方法估计H矩阵,进行图像拼接-Using sift algorithm to obtain the matching points between images, and rance method to estimate the H matrix, the image mosaic
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使用FLANN(近似最近邻算法)实现图像特征的匹配,其中图像特征使用SIFT提取,算法能实现单应性匹配需求。-
FLANN (approximate nearest neighbor algorithm) is used to match the image feature, and the image feature is extracted using SIFT. The algorithm can achieve the homography matching requirement.
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结合PCA的尺度不变特征变换(SIFT)算法,正确率可以达到98%,粒子图像分割及匹配均为自行编制的子例程。- Combined with PCA scale invariant feature transform (SIFT) algorithm, Accuracy can reach 98 , Particle image segmentation and matching subroutines themselves are prepared.
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VLFeat是一个跨平台的开源机器视觉库,它囊括了当前流行的机器视觉算法,如SIFT, MSER, HOG, 同时还包含了诸如K-MEANS, Hierarchical K-means的聚类算法。它由C语言编写,并提供了Matlab接口及详细的文档。当前最新的版本是VLFeat 0.9.18 。(The VLFeat open source library implements popular computer vision algorithms specializing in image un
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