资源列表
Match-point-correlation-coefficient
- 相关系数法的点匹配 void draw(int x,int y,Mat mat,Mat mod,int xx,int yy)通过十字丝表明匹配点 void ImgMarch(Mat s,Mat m,Mat roi,int x,int y)相关系数法匹配函数-Match point correlation coefficient method void draw (int x, int y, Mat mat, Mat mod, int xx, int yy) indicate the
detection-and-cell-technology
- 显微镜下细胞的检测与技术，该系统对显微镜下的细胞图片，通过图像处理技术检测出细胞，然后统计细胞个数。-Under the microscope detection and cell technology, the system of cells under the microscope image by image processing techniques to detect the cells and then count the number of cells.
cloud_to_mesh-master
- 三维点云图转换成网格图，代码完整，由cmake管理-Three-dimensional point cloud is converted into a grid map, code integrity, managed by the cmake
blur_img
- matlab程序：清晰图像变换为不同程度的高斯模糊图像程序-Matlab: clear image transformation for different levels of gaussian blur image process
car
- 车牌识别，首先对车牌进行提取，对车牌二值化，字符分割，字符识别-License plate recognition, license plate first extracted, license plate binarization, character segmentation, character recognition
blur_img
- matlab程序：清晰图像变换为不同模糊长度、模糊角度的运动模糊图像程序 -Matlab: clear image transform into different fuzzy length, Angle of motion blurred image
MBS
- 本代码是发表于CVPR2015上一篇效果非常好的MBS的显著性目标检测的程序，很有参考价值-The code is published in the significant target detection program CVPR2015 a very good effect on the MBS, a good reference value
Equalizer
- Equalizer 是标准的中间件并行创建和部署基于OpenGL的应用程序。它使应用程序能够从多个显卡，处理器和计算机利于规模的渲染性能，外观质量和显示尺寸。均衡器在任何应用程序运行未经修改的可视化系统从一个简单的工作站，以大型图形集群，多GPU工作站和虚拟现实装置- Equalizer is the standard middleware to create and deploy parallel OpenGL-based applications. It enables applicat
Desktop
- a imread( 1.jpg ) 图像imread后，a已经是矩阵了(彩色的3维，灰度2维) matlab操作数据以矩阵为基础，也就是计算都是矩阵啦-graph matching
dgxfgc
- 等高线赋值：根据第一根等高线赋高程,一次给多个等高线赋值- elevation contours: Function: Fu elevation contour lines according to the first root
improved_CV_model
- 改进CV模型，可以实现模型的加速演化。提高模型的分割效率。-The improved CV model can realize the accelerated evolution of the model. Improve the segmentation efficiency of the model.
lrr
- 聚类分析是数据挖掘研究领域中一个非常活跃的研究课题) 本文重点分析了高维度数据的自动子空间聚类算法-Cluster analysis is a data mining research area in a very active research topic) This paper focuses on automatic subspace clustering algorithm for high dimensional data