Master the development of time

图像处理初步，包括线性变换，几何变换，边缘检测-Preliminary image processing, including linear transformations, geometric transformations, edge detection

提供强大的图像处理功能，完全源代码公开， 包括旋转，放大，缩小，自动校正，选择范围，裁剪，自动去除黑边，镜像等等功能。提供技术支持，最适合应用于扫描后的图像处理 开发本控件原本就是应用于扫描后的图像处，方便使用-provide a powerful image processing functions, complete source code is open, including rotating, zooming, narrow, automatic calibration choice, cutting, automatic black border removal, image and so on. Provide technical support, Scanning the most suitable for the development of the Image Processing Control was originally applied to the scanned images, ease of use

理想高通滤波,最后显示处理结果. 直接解压后将图片和程序放在同一个文件夹里.-ideal high-pass filter, the final results showed. Photo will be directly extracted and procedures on the same document folder.

Matlab Toolbox 进行摄像机标定,在Matlab中使用的工具箱-Matlab Toolbox for camera calibration, used in the Matlab toolbox

这是有关计算机图形学中一个算法的实现原码，是有visual c++开发的-this is a computer graphics algorithms to achieve the original code, is the development of the visual c

线特征的hough提取程序，很不错的，自己试过，绝对可用-Line Features hough the process of extraction, very good that he tried to absolutely available

在vc++中，使用单文档程序，对数字图像进行拉普拉斯变换。供有兴趣的朋友学习-In vc++, The use of single-document procedures Laplace transform digital images. For interested people in learning

C++ Builder环境下读取bmp图像，这种源码很少见，很有用哦-C Builder environment reading bmp image, which rarely see the source code, useful oh

This file contains the function body for the watershed algorithm.Algorithm reference: L. Vincent and P. Soille, "Watershed in digital spaces: An efficient algorithm based on immersion simulations"-This file contains the function body for th e watershed algorithm.Algorithm reference : Vincent L. and P. Soille. "Watershed in digital spaces : An efficient algorithm based on immersion SIMU Doping "

先对图像进行开闭滤波，再使用分水岭分割图像，然后使用FCM对初始分割进行聚类，得到最终分割结果，对医学图像效果比较好。-First opening and closing image filtering, re-use watershed segmentation images, then use the FCM clustering of the initial partition, the final segmentation results, the medical image is better.