搜索资源列表
cvwork_correlation
- 使用vc++6.0和opencv1.0实现的模板与目标图片的匹配,用模板图像通过依次与图像的重叠区域进行相似度比较,将相似度最大的区域作为匹配目标区域。得出最后的匹配结果-Using vc 6.0 and opencv1.0 achieve the target image matches the template, using the template image followed by image overlap region with similarity comparison, simi
target-recognition-
- 一种新的目标识别算法,它是把模板匹配 思想和性能优异的思维进化计算结合起来,在均匀颜色空间上匹配。-A new target recognition algorithm, which is the template matching Thinking and performance Mind Evolutionary Computation combined to match the uniform color space.
opencv-pipei
- opencv 轮廓提取和模板匹配,可以从目标图像中找出要匹配的小图片部位-opencv contour extraction and template matching, you can find out from the target image to match the small image parts
Match-Template
- 这个程序详细描述的图像的各种边缘检测的方法与实验操作-This program detailed descr iption of the image edge detection of various methods and experimental operation
EmailTransfer
- 邮件自动匹配功能。给出相应的模版,能自动匹配成相应的邮件。-E-mail auto-matching. Given the appropriate template to automatically match the corresponding message.
lianma
- 利用链码进行图像匹配,对待匹配图像和模板图像提取链码-Chain code for image matching, treat match the image and the template image extraction chain code
OMatchhp
- 利用OpenCV中的模板匹配来匹配配模板和图片,找出图片中含有的模板图像 -Template matching in OpenCV to match with the template and pictures to identify the picture contains the template image
Match-Template
- 用于模版匹配1 对于一些初次学习图像处理的同学比较有用-Useful for edge detection image processing for some initial learning students
loadImage3
- opencv初学者第三课,用来匹配模板图片和原始图片,并用方框标出,同时显示模板位置-opencv beginners lesson, to match the template images and the original picture and framed display template location
templematching
- 模板匹配: 使用源图像模板匹配目标图像验证是否同一对象-Template Matching: use a source image as template to match target image to verify is same object or not
CachedFrame
- Made some changes to the comments to match the comments from other modules.Synchronized file with UMTS version 3.2.0. Updated coding template.
template_match
- opencv模板匹配小练习,适合初学者,有助于理解匹配-opencv template matching little practice, suitable for beginners, help to understand the match
aimlblofjq
- 一个最简单的aiml文件如下: <?xml version="1.0" encoding="GB2312"?> <aiml> <category> <pattern>你好</pattern> <template>好</template> </category> </aiml> 1. <?xml version="1.0" encoding="GB2
biolalage
- 1. think元素 型如: <think><set name="topic">Me</set></think> 放置在template元素里面,表示一旦用户的输入匹配到该category时,再回复应答的同时,给一个变量赋值,这里也就是把Me记再脑子里,以后就可以用<get name=”topic”/>来取出先前记住的内容。 2. <star/>表示*,比如有一个匹配模式是<pattern>* 你 好
MyMatch
- 图像模板匹配,分别设置两个ROI,基于灰度值得匹配-A template image match based on gray value set to 2 ROI seperately
FastMatch_v1
- "Fast-Match: Fast Affine Template Matching" cvpr2013Fast_Match, title={Fast-Match: Fast Affine Template Matching}, author={Korman, Simon and Reichman, Daniel and Tsur, Gilad and Avidan, Shai}, booktitle={Computer Vision and Pattern Recogni
OnRecogMatch
- 根据图象模板,在待匹配的图象中找到匹配的位置-According to the image template to be matched in the images found to match the location of
gougou23201016
- 实现对运动物体进行实时的检测,并且可实现运动目标物体与原始模板之间的匹配-To achieve real-time detection of moving objects, and can realize the moving target object and the match between the original template
DTW
- DTW算法的程序,申请两个n*m的矩阵D、d,分别为累积距离和帧匹配距离。这里n和m为测试模版与参考模版的帧数。然后通过一个循环计算两个模版的帧匹配距离d。接下来进行动态规划,为每个格点 (i,j)都计算其三个可能的前续格点的累积距离D1,D2,D3。考虑到边界问题,有些前续格点可能不存在,因此加入一些判断条件最后利用最小值函数min(),找到三个前续格点的累积 距离作为累积距离,与当前帧的匹配距离d(i,j)相加,作为当前格点的累积距离。该计算过程一直达到格点(n,m),并将D(n,m)输出,
TemplateSubPatternAssociation
- A class to contain a match pattern and it s corresponding template.