资源列表
VC_Harris_detector
- 使用vc开发的harris算法源代码，对进行特征匹配研究的同仁有借鉴作用。-use vc harris development of the algorithm source code to match the features of the study are useful colleagues.
KMeans3-based-opencv
- 基于OpenCV的K-均值算法,用于聚类分析,如图象的颜色聚类,生成相关的颜色表等.-the K-means algorithm for clustering analysis, such as image color clustering, Formation of color, and so on.
Histogram_HSV_36
- 求取彩色图象的HSV直方图,用于彩色图象的颜色特征提取.该算法基于OpenCV.-strike HSV color image histogram, Color image for the color feature extraction. The algorithm is based on OpenCV.
TextureSpectrum256
- 基于纹理谱的图象特征提取程序,用于图象与视频的分析与识别,该算法基于OpenCV.-based on the texture spectrum image feature extraction process for image and video analysis and identification, The algorithm is based on OpenCV.
scanf
- 计算机图形学算法编程扫描装换多边形线算法-computer graphics programming algorithm for scanning equipment polygonal line algorithm
ellipsefit
- 实现椭圆拟合的matlab程序，很不错，我的觉得比较有用-Matlab fitting procedure quite well, and I think that the more useful.
MapX_Demo
- Mapx在delphi下的开发样码,可以自由下载-Mapx delphi in the development of sample code can be downloaded free
SoftAssign_Procrustes_Matching
- 提供一个算法类，算法实现基于Softassign结合Procrustes距离的点对匹配方法-provide an algorithm category, Algorithm-based Softassign Procrustes distance from the light points of matching method
MIFncObject
- 刚体配准方法中，通常使用互信息函数作为相似性测度，此类提供计算的封装。-rigid registration method, which is commonly used as a mutual information function similar measure, the provision of such calculation package.
Powell_Search
- 刚体配准方法中，通常使用Powell搜索方法来做参数优化方法，此类提供封装的Powell方法-rigid registration method, commonly used search methods do Powell parameter optimization method, Packaging for such methods Powell
Thin-plate_Registration
- 使用薄板样条函数，完成点对的非刚体配准方法。此类提供算法的封装。-use thin-plate spline function, the completion point of the non-rigid registration method. Algorithm for such packaging.
fast_distance_map_caculate
- 使用边缘跟踪，种子填充等算法提取图像边界，然后使用并行的方法来计算图像的距离图。-using edge tracking and seed filling algorithm to detect the edges of images, then use the parallel approach to the calculation of the distance between the image map.