Grid

BMP图像边缘提取后 根据边缘点集直线拟合(BMP image edge extraction fitting a straight line)

说明：  掌纹识别palm print recognition software（gray processing, image filtering, detection angle HARRIS, wavelet decomposition. Heat extraction zone, the function of mathematical ecology ）(Palmprint identification palm print recognition software (gray processing, image filtering, detection angle HARRIS, wavelet decomposition. Heat extraction zone, the function of mathematical ecology))

windows下c++鱼眼校正，debug内exe可直接运行看结果。内附参考文献，更详细文献可见论文《超大广角畸变图像的校正和展开》。(C++ fisheye correction under windows, debug within exe can run directly to see the results. With reference to the literature, more detailed literature can be seen in the paper "super wide-angle distortion image correction and expansion".)

用C++编写的实现GVF的活动轮廓模型的提取，值得你参考(Extracted with implementations written in C++ GVF active contour models, it is worth your reference)

边缘检测 Edge Detection Edge Detection(Edge Detection)

图像变换,处理图片的变换及反走样处理，包含ＶＢ和ＶＣ的源文件(Image transformation, to deal with the change of image and anti-aliasing processing, VB and VC contains source files)

分类程序的实现，可在vc++平台中运行，方便大家对算法的熟悉与学习(Classification procedures to achieve, can be run in vc++ platform to facilitate learning of the algorithm are familiar with)

输入一个带权无向图的顶点数、边数、各条边信息（两个顶点和权值），建立该图的邻接矩阵结构，输出该邻接矩阵。将上述无向图邻接矩阵转换为邻接表结构，输出该邻接表；根据该邻接表对无向图进行深度优先遍历序列和广度优先遍历序列，并输出遍历结果；用prim算法实现构造该带权无向图的最小生成树，并将该最小生成树的各条边信息输出。(Enter a weighted undirected graph with vertices, edges, each of the side information (two vertices and weights), the establishment of the adjacency matrix structure, the output of the adjacency matrix. The above undirected graph adjacency matrix into adjacency list structure, the output of the adjacency list according to the adjacency table undirected graph depth-first traversal sequence and breadth-first traversal sequence, and outputs through the results using prim algorithm construct the weighted undirected graph minimum spanning tree, and the minimum spanning tree information on respective sides of the output.)

基于边缘特征的图像配准算法源码 基于边缘特征的图像配准算法是将不同时间、不同的传感器（成像设备）或不同条件下（天候、照度、摄像位置和角度等）获取的同一场景的两幅或多幅图像根据其边缘特征进行匹配、叠加的处理，最终生成一幅全景图像的方法。该方法具有抗噪性强，匹配速度快，误匹配率低，适用于多种类型的图像等优点，主要可以运用于以下领域： （1）军事研究领域，如飞行器辅助导航系绞、武器投射系统的末制导以及寻地等应用研究； （2）医学图像分析，如数字剪影血管造影DSA血管造影术、肿瘤检测、白内障检测、CT、MRI、 PET、 SPECT图像结构信息融合； （3）模式识别，如特征识别、波形分析、签名证实、目标物运动跟踪、序列图像分析等； （4）计算机视觉，可用于目标定位、自动质量控制等； （5）遥感数据分析，多电磁波段图像信息融合，如多谱段的等场景分类、定位和识别定义好的或已知特征的场景、自然资源监控、核生长监控、市区增长检测等。 本算法实现使用VC++6.0为开发环境，目前只支持灰度图像，感兴趣的朋友可以进一步扩展。(Image registration is a fundamental problem in image processing, which is a process to match two or more images of the same scene taken at different times, from different viewpoints, or by different sensors. Image registration is an important technique for a great variety of applications such as medical image analysis, computer vision, remote image data analysis, image information fusion, and the recovery of the 3–D characteristics of a scene.)

该数字图像处理文件有很强的修改能力，可以仔细的分析每一个频域不同条件下的实验结果分析。有很强的处理图像能力(The digital image processing of documents has a strong ability to change and be more careful analysis of each under different conditions, a frequency-domain analysis of the experimental results. Has a strong ability to deal with images)