matlab_基于象素的图像配准程序,很好使用,精度也很高,要用的就下载吧!...

基于轮廓的形状特征提取 1)该程序在VC＋＋6.0下编译通过； 2)测试图片说明：（图像路径名请在main函数中fp=fopen("1.bmp","rb")中设定） 64×64 24bit BMP： 图像1、2用来验证旋转图像识别；图像1、3用来验证平移图像识别；图像1、4用来验证缩放图像识别； 120×120 24bit BMP： 图像5、6用来验证平移图像识别；图像7、8用来验证旋转图像识别； 3)结果说明： MCS.dat保存了Mountain Climbing Sequence。 -Based on the outline of the shape feature extraction 1) the program in VC 6.0 under the compiler through 2) Test Photo Caption: (image path name in the main function fp = fopen (1.bmp, rb) set) 64 × 64 24bit BMP: image 1,2 to verify rotating image recognition image 1,3 to verify translational image recognition image 1,4 to verify scaling image recognition 120 × 120 24bit BMP: images used to verify translational 5,6 image recognition images 7,8 rotate images used to verify identification 3) The results indicate that: MCS.dat preserved Mountain Climbing Sequence.

用一种快速有效的算法实现照片的全景拼接,内附样例照片可直接验证算法的准确性-With a fast and efficient algorithm of the panoramic photo stitching, pictures can be directly attached sample to verify the accuracy of algorithm

hough变换中，进行了hough变换，峰值检测，找非零点，找到相关像素后，还要执行这个操作，才能实现功能-hough transform for the hough transform, peak detection, to find non-zero, after finding the relevant pixel, but also the implementation of this operation, to achieve functional

SUSAN-based functions to detects image edges and their orientation-SUSAN-based functions to detects image ed celebrated and their orientation

Cximage Linux port tested in FC8

Visual C++MATLAB图像处理与识别实用案例精选之　图像阈值变换　算法的源程序，含标准测试图片-Visual C MATLAB image processing and recognition of practical cases selected images threshold transform operator Law of the source, including standard tests Photo

这是有关图像处理的文件，是用vc 编写的 ，可以供大家参考-This is the image processing of documents is prepared vc, you can for your reference

对图像进行对角镜像处理的源代码,图形变换-right image right angle mirror of the source code, graphic transformation

图像的颜色处理，包括颜色抖动，颜色转换等。-Deal with color images, including color dithering, color conversion.

图像配准程序,含有图像配准的这种算法以及检验程序-Image registration procedures, containing this image registration algorithm and testing procedures