ITKbrain

我写的贝叶斯fusion的Visual C+++源码，简明易懂，提供参数说明 可直接使用。 (The Bayesian fusion the Visual C+++ of what I wrote source, easy-to-understand parameters can be used directly.)

根据D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis 以及 C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision.这两篇文献提供的方法编写的图像分割代码，作者是 Chris M. Christoudias, Bogdan Georgescu，代码经我看了后加了丰富的中文注释，希望可以给各位带来阅读上的方便。 基于meanshift的聚类分割方法包括滤波、区域融合等操作，通过调整sigma和sigmar来调整分割效果。(According to D. Comaniciu, P. Meer: Mean Shift: A robust approach toward feature space analysis, and C. Christoudias, B. Georgescu, P. Meer: Synergism in low level vision. These two documents prepared by the methods provided by image segmentation code , the author is Chris M. Christoudias, Bogdan Georgescu, after I read the code, add a rich Chinese notes, hoping to bring you the convenience of reading. Segmentation method based on clustering meanshift including filtering, regional integration and other operations, and by adjusting the sigma sigmar to adjust segmentation results.)

对CANNY算子进行改进，其中详细的分析了CANNY算子的原理，已经应用改进的canny算子进行边缘检测，效果较好(CANNY operator improvements, including a detailed analysis of the principle of CANNY operator has been applied to improve the canny operator edge detection, better )

实现图像的滤波、锐化、边缘检测、微分处理及图像平滑(Image filtering, sharpening, edge detection, differential processing and image smoothing)

多边形填充 多边形裁剪 自定义多边形区域 自定义裁剪区域(Polygon fill polygon clipping custom polygon area custom crop area)

车型识别图像处理MATLAB代码可运行适合新手入门只用(car recognization adapted rookie study playplay)

利用visualC++和图像处理的知识，编写程序对果蔬进行自动识别(Using visualC++ and image processing knowledge, write a program for automatic identification of fruits and vegetables)

经典矩量法点匹配程序，重推导，注释说明详细(Classical point matching moment method procedure)

利用Artoolkit实现了虚拟现实的算法，VS2008下测试通过(Use Artoolkit algorithm to achieve a virtual reality, VS2008 under test)

本代码可以实现图像的维纳滤波，经过调试无错误，对于学习图像处理有较好帮助。(This code can achieve the image filtering, error-free through the debugging, better for learning image processing help.)