提出了基于边缘特征的亚像素投影配准算法,法引入新的图像相似性评价函数 ― 均方误差函数(Mean Sequare Er ron ,MSE)...

JPEG解码程序，包括BASELINE 和 PROGRESSIVE 两种常用格式。-JPEG decoding procedures, including BASELINE and PROGRESSIVE two common format.

模式识别和图像处理中特征提取的C++源代码，非常容易集成和使用！-pattern recognition and image processing feature extraction of C source code, and is easy to integrate and use!

计算几何(C描述)第二版教材的配套程序,用C语言实现了本书的主要算法.-Computational geometry (C described) in the second edition of materials matching procedures, using C language to achieve the book

非常好的 标定exe程序(特别对于初学者并可亲自做实验感受) 功能:1可以进行内外参数标定.2并有棋盘式图片可以打印,对于初学者可方便做实验.3内有拍好的相片可直接使用.4还有readme说明,不过本程序操作十分简单. 希望能对您的学习有所帮助!

用于各种图像分割的算法 ，隐痛上传，从上面的边缘检测，二值化，区域分割一些经典的算法来加深对图像分割的理解。粗略分析了这些算法的优点很不足。对于课题算法的选取起了很大的帮助-for various image segmentation algorithm secret anguish uploads from above the edge detection, two values, Segmentation some classical algorithm for image segmentation deepen understanding. Rough analysis of the advantages of these algorithms are inadequate. Algorithm for the selection of topics has been most helpful

用C＋＋编写的一个数字图象处理平台，头文件 包含变量声明和函数声明-with C++ in the preparation of a digital image processing platform, the first document contains variable declarations and function declaration

此源码包括对图像的边缘检测、梯度锐化和微分运算等图像处理的操作。-This source includes the image edge detection, gradient operator, such as sharpening and differential image processing operation.

将TIF格式转换成BMP格式图像的程序.-TIF format will be converted into BMP format images procedures.

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

通过遗传算法选择道路图象分割的最佳阈值,阈值的选择采用最大类间方差的办法,程序运行结果达到相当理想的效果-Through the genetic algorithm to choose the best road image segmentation threshold, the threshold was chosen as the maximum between-cluster variance approach, the program results achieved the desired results rather