搜索资源列表
opencv-shift-graphics-match
- opencv的shift图像匹配程序 实现了角点检测 特征点检测 图像匹配-opencv shift graphics match
find_obj
- surf 方法 直接能运行 配上opencv 图像特征点匹配 sift方法的改进版本,在时间上面大大提高同时在光照方面比sift要好很多-Methods can be run directly coupled surf opencv image feature point matching method sift improved version of the above at the time of greatly increased both the light much better th
feature-matching-based-on-opencv
- 基于opencv来简单实现图像处理中的特征点提取和匹配-Opencv to simple implementation based on image processing feature extraction and matching
OpenCV_VC6.0_surf
- Visual C++ 6.0平台基于OpenCV的SURF图像特征点的检测和匹配源代码,能正确的实现图像特征点的检测和匹配功能,对研究图像特征点匹配非常有帮助。-The Visual C++ 6.0 platform is based on OpenCV SURF image feature points detection and matching of source code, can correct the image feature point detection and matchin
cvut_test
- 立体视觉中的稀疏点重构程序 特征点匹配后得到重构图像,对立体视觉的研究有很大的指导性作用-In the stereo vision,the reconstruction of the object based on the two sides of the object.
SIFTTest3
- 实现对图像的sift特征点检测,能够对图像添加噪声、旋转、缩放,检验sift算法效果,实现两幅图像间的sift特征点匹配。-Sift feature point detection on the image, you can add noise on the image, rotate, zoom, testing the effect of sift algorithm, sift feature point matching between two images.
SIFT-feature-matching-
- SIFT 特征匹配算法是目前国内外特征点匹配研究领域的热点与难点,其匹配能力较强,可以处 理两幅图像之间发生平移、旋转、仿射变换情况下的匹配问题,甚至在某种程度上对任意角度拍摄 的图像也具备较为稳定的特征匹配能力。该算法目前外文资料较多,但中文方面的介绍较少。为此 我撰写了这篇文档,以帮助国内的研究学者尽快入门,以最快的速度去体验 特征匹配算法是目前国内外特征点匹配研究领域的热点与难点,其匹配能力较强,可以处 理两幅图像之间发生平移、旋转、仿射变换情况下的匹配问题,甚至在某种
sift
- sift算法匹配图像特征点(opencv)-sift algorithm for image matching feature points (opencv)
opencvorb
- 利用Orb算法实现图像特征点的提取,并且通过前后两帧之间的特征点进行特征匹配,为视频稳像、图像融合以及图像识别提供前提条件。-Detecting feature points using Orb algorithm, then matching the points with the detected points frames.That method provide one new way to video stablization ,image fusion and image recog
45398761sift
- 本代码是应用sift算法进行的特征点匹配与配准,可以应用于图像拼接,人脸识别等等,用法非常强大。可以运行-This code is matched with the feature point registration application sift algorithm can be applied to the image stitching, face recognition, etc., usage is very powerful. You can run
libpano13-2.9.19.tar
- 全景拼接程序 可找到图像中的特征点 通过特征点匹配 将多角度照片拼接起来形成全景照片- This program is free software you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, version 2.
Suaf-stitch
- 使用opencv完成图像拼接,使用suaf特征点匹配; 有详细的中文注释; 有中间过程(画出特征点、特征点匹配、旋转、曝光修正等); VS2012工程,使用的是opencv2.4.11; 注意重新配置工程关于opencv的信息;-Use opencv complete image stitching, using suaf matching feature points a detailed Chinese annotation an intermediate process
SIFT_and_ransac
- sift-and-ransac结合的图形图像特征点匹配于删除误匹配点-Graphic image feature point sift-and-ransac binding matches delete mismatching points
PEIZHUN
- 使用FLANN进行特征点匹配,完成图像配准功能-FLANN performed using feature point matching, image registration function is completed
imagestitching
- 实现了图像的简单拼接。首先寻找特征点,然后计算描述子(特征向量),对寻找到的特征点进行匹配,并塞选匹配结果,然后计算透视 矩阵,将其中一幅图进行透视变换,然后将图片合成。对一些简单的图片比较有效。仅供参考学习。(Realize the simple stitching of the image. First, find the feature point, and then calculate the descr iptor (eigenvector), match the feature po
code1
- 特征点提取及图像匹配,局部图像特征提取匹配(Feature point extraction and image matching, local image feature extraction matching.)
quickly match
- 基于亮度/色彩一致性,在SURF算法的基础上提出了一种快速图像特征点匹配算法,可以缩小特征点匹配所需的运行时间,提高正确匹配率。(Based on the brightness / color consistency, a fast image feature point matching algorithm based on SURF algorithm is proposed, which can reduce the running time of feature point matchi
opencv3.2_SIFT+flann
- 本程序用于图像拼接,使用了SIFT特征点匹配,加上了加权融合算法去除了明暗接缝(This program is used for image stitching, using SIFT feature point matching and adding a weighted fusion algorithm to remove the bright and dark seams)
FasterSurf
- 一个图像拼接框架。切换注释与未注释代码可实现不同检测器与描述子的组合。默认使用SURF+BRIEF,通过预设重叠区域比例排除非重叠区域特征点的检测,提升特征点检测速度,减少误匹配。(An image stitching frame. The switching annotation and the non - annotated code can implement the combination of different detectors and descr iptors. Using SU
SURF探测器拼接两张图像以创建全景的openCV实现
- 基于SURF的图像拼接,全景图像筛选特征点,进行匹配刷选转换(Image mosaic based on SURF panoramic image filtering feature points matching selection switch)