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[Graph Recognize] match DL : 1: 一种具有旋转不变性的模板匹配方法,以前做项目使用过，效果不错，希望有用-A rotation invariant template matching method, in the past used to do the project, well, I hope useful
Update : 2025-02-17 Size : 432kb Publisher : lidawei
[Graph program] shapMatch DL : 0: 本文对形状匹配的方法进行了回顾。介绍了一些形状表示方法, 其中主要是形状简化的方法。形状匹配的方法可以分为基于各种变换不变量的形状匹配方法和基于局部特征的形状匹配方法, 并根据这一分类介绍了很多有代表性的匹配方法。-In this paper, shape matching methods reviewed. Introduce a number of shape representation method, which is mainly the shape of simplification. Shape matching methods can be divided into a variety of transformation based on the shape invariant matching methods and based on local characteristics of shape matching methods, and in accordance with this classification introduce a lot of representative matching method.
Update : 2025-02-17 Size : 222kb Publisher : happyopencv
[Special Effects] SIFT_YantaoNoemie DL : 0: 图像特征匹配算法 SCALE INVARIANT FEATURE TRANSFORM -Image feature matching algorithm SCALE INVARIANT FEATURE TRANSFORM
Update : 2025-02-17 Size : 1.2mb Publisher : weiweishu
[Special Effects] InvariantLocalFeatureforImageMatching DL : 0: Invariant Local Feature for Image Matching,主要是介绍了一下图像副本检测的系统，先对图像提取sift特征，再用LSH匹配-Invariant Local Feature for Image Matching, mainly introduced a copy of what the image detection system, first sift the characteristics of the image extraction, and then match the LSH
Update : 2025-02-17 Size : 1.62mb Publisher : 潘自建
[2D Graphic] Log_polartransformation DL : 0: Log-polar transformation :The function emulates the human "foveal" vision and can be used for fast scale and rotation-invariant template matching, for object tracking etc.download and install opencv 1.1 pre
Update : 2025-02-17 Size : 1kb Publisher : rahman
[GIS program] sc_demo DL : 0: ShapeContext的著名demo 结合介绍对shapecontext有较好的理解-Demo for shape context, a famous descriptor for keypoints matching, which has rotation and scale invariant.
Update : 2025-02-17 Size : 91kb Publisher : 桑基韬
[Special Effects] SIFT DL : 0: 两份SIFT的重要资料：Distinctive Image Features from Scale-Invariant Keypoints（by David G. Lowe）,SIFT特征匹配技术讲义(by 赵辉)-SIFT two important information: Distinctive Image Features from Scale-Invariant Keypoints (by David G. Lowe), SIFT feature matching technical notes (by Zhao Hui)
Update : 2025-02-17 Size : 1.97mb Publisher :
[matlab] Invariant_Line_Segment_Matching DL : 0: function Invariant_Line_Feature_Matching ___DESCRIPTION___ Compare segmented line pairs as 4 dimentional line pair features ( Q1 , Q2 , Drelative , D? ) Example : Invariant_Line_Feature_Matching ( ) ___REFERENCE___ Paper 1 : Line Feature Matching Technique Based on an Eigenvector Approach Park, Lee, Lee - Ideal - CV and Im. Und. - 77, 263-283 - (2000)- function Invariant_Line_Feature_Matching ___DESCRIPTION___ Compare segmented line pairs as 4 dimentional line pair features ( Q1 , Q2 , Drelative , D? ) Example : Invariant_Line_Feature_Matching ( ) ___REFERENCE___ Paper 1 : Line Feature Matching Technique Based on an Eigenvector Approach Park, Lee, Lee- Ideal- CV and Im. Und.- 77, 263-283- (2000)
Update : 2025-02-17 Size : 27kb Publisher : Mehmet
[Communication] projectprogaram DL : 0: Recognition of visual patterns and characters are independent of position, size, and orientation in the visual field has been the goal of much recent research. The method presented in this paper meets all these condition. An off-line signature matching system which is based on Hu moment invariant method is presented here. Signature matching uses a four - steps process. In first step the scanned or captured color images are initially converted to grey scale. Second step performs normalization and digitization of the original signature. Noise reduction (also called “smoothing” or “noise filtering”) is one of the most important processes in image processing is performed in third step and then moment invariant vectors are obtained in the last step. Signature matching system is implemented using MATLAB and ability of the system can be increased by using additional features in the input data set.
Update : 2025-02-17 Size : 8kb Publisher : shivshankar mishra
[Windows Develop] 67506282mahalanobis DL : 0: 马氏距离的仿射不变性删除误匹配特征点对，据此可求取2幅源图像间的仿射变换参数-Mahalanobis distance of the affine invariant features remove the false matching points Yes, according to the source to obtain two parameter affine transformation between images
Update : 2025-02-17 Size : 1kb Publisher : yimeng
[matlab] invriablemoment DL : 0: 不变矩是模式识别里面很重要的一种技术，它可以用于提取不变性特征，从而进行模式识别，广泛用于图像处理当中，如图像特征匹配-Moment invariant pattern recognition which is a very important technology that can be used to extract invariant features for pattern recognition which is widely used in image processing, such as an image feature matching
Update : 2025-02-17 Size : 4kb Publisher : zj
[Special Effects] image_matching DL : 1: 实现了三种图像匹配算法 1：归一化互相关匹配算法 2：基于Hausdorff距离的图像匹配算法 3：图像不变矩匹配算法-Three matching algorithms to achieve 1: normalized cross correlation matching algorithm 2: the image matching algorithm based on Hausdorff Distance 3: Image Invariant Moment Matching Algorithm
Update : 2025-02-17 Size : 12kb Publisher : 赵宏磊
[Special Effects] Image DL : 1: 博士论文：图像特征提取、匹配和新视点图像生成技术研究关键词：基于图像的绘制；虚拟现实；新视点图像生成；宽基线图像匹配；仿射不变量直线段匹配；立体视觉-Dissertation: Image feature extraction, matching and the new viewpoint image generation technology Keywords: image-based rendering virtual reality new viewpoint image generation wide baseline image matching affine invariant matching line segments stereo vision
Update : 2025-02-17 Size : 5.81mb Publisher : qinjw
[Special Effects] LBP-SIFT-image-matching-algorithm-combined DL : 0: SIFT和旋转不变LBP 相结合的图像匹配算法(数字图像处理/图像匹配）-SIFT and LBP combined rotation invariant image matching algorithm (digital image processing/image matching)
Update : 2025-02-17 Size : 589kb Publisher : 马蓉琼
[Special Effects] ObjectMatchingwithAffine-Invariant DL : 0: 基于局部仿射不变的特征匹配算法，包含全部.m文件，很有价值。-Based on local affine invariant feature matching algorithms, including all. M file of great value.
Update : 2025-02-17 Size : 671kb Publisher : wang
[Special Effects] shape-matching-cluttered-scenes- DL : 0: 旋转不变非刚性的图像匹配。代码为matlab源码，代码注释详细，可以通过代码上的链接找到原始文献，以作详细学习-Rotation-invariant non-rigid image matching. Matlab source code, code comments in detail, you can find links to the original code on the literature, for detailed study
Update : 2025-02-17 Size : 313kb Publisher : joe
[Special Effects] Fast-Rotation-invariant-Template DL : 0: 图像梯度方向应用干旋转不变性模板匹配时存在计算量较大的问题，由此提出一种改进的基于梯度方向码的旋转不变模板匹配方法，通过计算积分直方图降低统计直方图的计算填，采用像素跳跃的匹配方法减少大量无效的匹配运算。实验结果表明，该方法在保证匹配准确性的前提下，匹配速度提高了3倍至6倍，可以达到实时性要求。-it uses integral histogram to reduce the computing COSTS of computer histograms，and uses pixel-jump method to reduce a lot of ineffective matching operalions．Experimental result shows that the method Can speed up from 3 to 6 times in the premise of ensuring matching accuracy，SO it Can meet real-time requirement．
Update : 2025-02-17 Size : 309kb Publisher : chen
[Special Effects] Rotating-template-matching DL : 0: 一种具有旋转不变性的模板匹配方法圆投影-A rotation invariant template matching method
Update : 2025-02-17 Size : 432kb Publisher : liu
[Special Effects] Shape-matching-with-Zerinike-moments DL : 0: 结合Zernike矩的多尺度模板形状匹配，该算法对输入图像进行预处理后提取目标轮廓，经过归一化处理得到目标形状的平移、尺度不变的链状表达，再通过小波变换进行多尺度分析；引入Zernike矩，利用Zernike矩的特性，实现小波表达的旋转不变性，解决了小波变换对起始点的依赖。-Shape matching based on multi-scale template with Zerinike moments，The object shape representation is converted to a dyadic wavelet representation by wavelet transform. And then calculate the Zernike moments of wavelet representation in different scales. With respect to property of rotation invariant of Zernike moments and in consideration of Zernike moments as feature vector to calculate the similarity between the object and template image, the problem of dependency of starting point can be solved.
Update : 2025-02-17 Size : 1.25mb Publisher : 卢宠
[Special Effects] affine-invariant-moment DL : 0: 仿射图像匹配时候可以用到，需要已知先验知识，然后直接调用就可以了-Affine image matching can be used when the need is known a priori knowledge, then you can directly call the
Update : 2025-02-17 Size : 557kb Publisher : 董萍

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