LBP

说明：  图像处理-人脸识别技术：识别出图像中人物的五官形态，从而达到识别人脸的目的。(Image Processing-Face Recognition Technology)

本程序是运用脉冲耦合神经网络（PCNN）算法进行图像分割的一个实例。基于PCNN的图像分割是一种图像像素相似度临近相似性的图像分割方法，已被广泛应用于图像平滑，分割及边缘检测等图像处理领域。(This program is an instance of the algorithm for image segmentation using pulse coupled neural network (PCNN). PCNN-based segmentation of an image pixel similarity near the the similarity image segmentation method has been widely used in image smoothing, segmentation and edge detection image processing applications.)

包括基于SIFTGPU的sift特征提取，sift匹配，基于ransac误匹配点剔除等(SIFTGPU based sift feature extraction, sift matching, mismatching points based ransac removed, etc.)

ImageMagick® is a software suite to create, edit, compose, or convert bitmap images. It can read and write images in a variety of formats (over 100) including DPX, EXR, GIF, JPEG, JPEG-2000, PDF, PhotoCD, PNG, Postscript, SVG, and TIFF. Use ImageMagick to resize, flip, mirror, rotate, distort, shear and transform images, adjust image colors, apply various special effects, or draw text, lines, polygons, ellipses and Bézier curves.

其中用到了 timer控件

说明：  图像处理软件含帮助。毕业设计，旋转，线性变换，灰化，平滑，滤镜，反相等，功能全面！(image processing software with help. Graduation design, rotary, linear transformation, ash, smooth, filter, anti-equal, full functions!)

基于图像空间的素描效果生成技术，提供测试图片，利用sketch文件开始(Generation technology based on image space sketch effect)

中南大学数字图像处理上机实验指导书及参考答案，全部由本人编写，在MATLAB 6.5上运行通过。包括图像变换及频域滤波，空间域图像增强，图像边缘检测及参考图片，比网上流传的好的多，是学习图像处理的基础。(Zhongnan University of digital image processing on the experimental guide and reference book answers all prepared by me, MATLAB 6.5 to run through. Image Transform and including the frequency domain filtering and spatial domain image enhancement, edge detection and reference photographs, spread over the Internet much more study is the basis of image processing.)

说明：  在autocad2007环境中直接使用API就可以亮显实体的一个示例演示(This program demonstrates how to use ObjectARX API functions to highlight and unhighlight subentities of complex entities such as ACIS solids.)

这是一个比较完整的KPCA算法，通过这个算法可以快速的找到主要的特征向量进行主成分分析。(This is a relatively complete KPCA algorithm, this algorithm can quickly find the main feature vector principal component analysis.)