搜索资源列表
figer
- 指纹识别程序,它包括了直方图均衡,Gabor滤波图像增强,方向图过滤,纹理细化,特征提取及特征匹配。其中,特征匹配包含了3种匹配方法,非常值得研究。-Fingerprint recognition program, which includes a histogram equalization, Gabor filter image enhancement, pattern filtering, texturing, thinning, feature extraction and featur
RCP
- In this paper, we present an efficient feature matching algorithm to employ sparse reliable correspondence priors for piloting the feature matching proce-In this paper, we present an efficient feature matching algorithm to employ sparse reliable
finger(-C)
- 指纹图像增强、求方向图、二值化、细化、特征提取、特征匹配等算法 的c语言源程序,还有实例演示,本人千辛万苦才找来的, 提供给大家分享。 -Fingerprint image enhancement, seeking direction map, binarization, thinning, feature extraction, feature matching algorithm c language source code, as well as examples of pre
SIFT_VC
- SIFT算法,实现了SIFT特征的匹配。要运行得配置好opencv.-SIFT algorithm, realized the SIFT feature matching.To run the configuration well opencv.
matching
- 使用Harris Corner提取特征点,通过相关算法得到匹配结果后,再使用Ransac算法剔除错误匹配-Using Harris Corner feature point extraction, through the relevant algorithm matches, then use Ransac algorithms eliminate false matches
OpenCV_-image-feature-extraction
- OpenCV_局部图像特征的提取与匹配_源代码-OpenCV_ local image feature extraction and matching source code _
image-retrieval
- 基于内容的图像检索代码,运用底层颜色特征匹配检索图像,带有示例图片-Content-based image retrieval code, the use of low-level feature matching colors retrieve images with sample picture
SIFT
- 提取SIFT特征,进行特征提取和匹配,包括特征点的定位,特征点描述子的生成,特征点的匹配,-extract SIFT feature,and feature matching
matchSIFT
- 基于SIFT的特征匹配源代码,代码中含有对SIFT的最详尽表述,能让你更加深入的了解SIFT的工作流程,其中几个DEMO是SIFT的几个应用的例子-SIFT-based feature matching source code, the code contains the most detailed presentation on SIFT, allowing you to more in-depth understanding of the SIFT workflow, several DEM
opencv---sift
- 基于opencv的sift图像拼接算法,是特征匹配的一种,具有旋转、平移、遮蔽以及仿射不变形,广泛应用于图像拼接及图像特征匹配中-Based on the opencv sift image stitching algorithm, is a feature matching, rotation, translation, masking and affine deformation, is widely used in image stitching and image feature mat
Gabor_wavelet1
- 基于gabor小波变换的图像检索程序。有特征提取、特征匹配,以及结果返回。-On gabor wavelet transform based image retrieval process. There are feature extraction, feature matching, as well as the results returned.
822920IndexFileMain
- 索引文件 数据库 快速数据采集 减少像素计算 快速特征匹配 图像检索-Index file database fast data acquisition to reduce pixel calculation rapid image retrieval feature matching
image-matching--
- 首先对图像 进行高斯和 Wallis 滤波处理,然后采用简化 SIFT 算法进行特征点提取,最后通过特征点双向 匹配方法实现图像的精确匹配。通过对缺陷版图图像的试验验证了该方法具有匹配点数量 多、准确率高、无重复点等优点。-First of all Gaussian image filtering and Wallis and simplified SIFT feature point extraction algorithm, and finally through the fea
image-matching-
- 针对 128 维 SIFT 特 征向量,采用距离匹配和余弦相似度匹配相结合的测度方法,利用特征点方向一致性进一步降低误匹配率 . 实验结 果表明:改进算法对图像的缩放、旋转、光照、噪声和小尺度的视角变换均有较好的匹配效果 . 与原算法相比,在保 证匹配点数和匹配时间的基础上,改进算法对旋转、缩放、噪声模糊和光照变换的误匹配率平均降低 10%~20% , 对于小尺度的视角变换,误匹配率平均降低 5%. -For 128-dimensi
sift-based-on-edge-corner
- SIFT 由特征提取,特征描述符描述和特征匹配 3 部分构成,该算子特征提取数目庞大,建立特征描述符运算 量高,导致算法效率低。提出了一种 SEC( SIFT-Edge-Corner) 算法,在图像尺度空间提取角点代替 SIFT 特征点,并根 据角点是边缘曲率极值理论,预先采用 Canny 算子得到高斯边缘图像金字塔,再提取角点并进行尺度选择。实验结 果表明: 该算法在保障高准确率的前提下大幅度提高特征提取效率-By the SIFT feature extraction, fea
ICM2image_loop
- 对两帧图像进行ICM调试.包含内容:1估计姿态和摄像机内参数;2两幅图做四次金字塔;3利用输入特征点采用ransac算法估计姿态R, T。4sift特征匹配;5摄像机标定。-ICM images on two debugging. Contains: 1 Estimated posture and intrinsic parameters 2 two plans to do four pyramids 3 using the input feature points using ransac
SIFT_VC--can-be-directly-used-to-run
- SIFT特征匹配算法完整版,可直接运行,已经包含了所有的.h文件,链接了所需的.lib文件,具备所有dll文件,在VS2010上编译通过,生成的EXE文件可以在任何电脑上运行,不需要安装OPENCV和GSL,另外附加了一篇实验论文,可实现基本的特征点查找以及特征点连线。-The full version SIFT feature matching algorithm, can be directly run, already contains all of the. H file the req
KTL(1.3.4)
- 图像处理中的特征匹配算法,KTL特征跟踪算子的实现。参考论文:Good Features To Track-Image processing feature matching algorithm, KTL feature tracking operator implementations. Reference papers: Good Features To Track
SiftMatch
- 图像处理Sift 特征匹配算法。用到GSL库,需在 VS2010中的配置GSL才能正常运行。-Sift image processing feature matching algorithm. Use the GSL library, you need to configure the GSL in VS2010 to run properly.
siftPransac
- SIFT点提取,KD树特征匹配,再用随机抽样一致算法去除无匹配-SIFT extraction, KD tree feature matching, and then remove the non-random sample consensus algorithm matches