简单图形的生成，填充（比如直线、圆、拟合曲线等） 图像的处理（二值化、锐化、浮雕化、图片解压、压缩）...

批量转化模式--JIPG缩放程序 可以批量转化-Batch conversion mode- JIPG scaling procedure

人脸识别系统,你需要按照菜单一步一步才能实现识别!值得一看!-face recognition system, you need to step by step in accordance with the menu can be achieved recognition! An eye-catcher!

图象的检测，模式匹配的c代码，请大家仔细看里面的算法哦，希望会有收获吧。-image detection, pattern-matching c code, please carefully read the inside algorithm Oh, it is hoped that harvest.

基于YCrcb肤色模型的人连检测系统.用VC++实现.还包括人脸、眼睛、嘴巴的定位分割。-YCrcb color model based on the long-detection system. With VC. Also including face, eyes, Segmentation mouth positioning.

霍夫变换可以进行边值提取功能，在数字图像处理上功能强大-hough

一个全面的图像处理与分析软件源程序(可处理BMP,JPEG,Tiff等文件)-A comprehensive image processing and analysis of software source code (which can handle BMP, JPEG, Tiff and other documents)

本文提出了一种新的跨国家的障碍 检测技术为基础的立体视觉系统。 原始图像的预处理的高斯 过滤器和对比度限制的自适应直方图 均衡（ CLAHE ）方法来削弱作用 噪音，光线和对比度。哈里斯的角落位于与子像素精确。 -Cross-country intelligent vehicles always work in complicated environments with varying illuminations. The paper presents a new cross-country obstacle detection technology based on stereo vision system. The original images are preprocessed by Gaussian filter and contrast-limited adaptive histogram equalization (CLAHE) method to weaken the effect of noise, light and contrast. Harris corners are located with sub-pixel accurate. To guarantee the overall system real-time performance, feature-based matching techniques are studied and fundamental matrix is calculated based on random sample consensus (RANSAC). Also restrains are studied to eliminate pseudo matching pairs. Then data interpolation is introduced to build elevation maps. Edge extraction and morphological processing are concerned to accomplish obstacle detection. Experiment result

VC与MATLAB混合编程在图像处理中的应用-Mixed with the MATLAB programming VC in the application of image processing

本文提出了一种基于区域分割的分段线性变换方法，结合灰度直方图提供的有关灰度分布的统计信息 和图像提供的空间位置信息，利用各灰度区间把图像分割成不同的区域，检验要增强的目标是否落在某 灰度区间对应的图像区域内，从而加快了调整灰度区间的过程，提高了算法的执行效率。-dddddddddddddddddddddddddddddd

深入浅出介绍计算机视觉的最新动态。内容包括： * Camera calibration using 3D objects, 2D planes, 1D lines, and self-calibration * Extracting camera motion and scene structure from image sequences * Robust regression for model fitting using M-estimators, RANSAC, and Hough transforms * Image-based lighting for illuminating scenes and objects with real-world light images * Content-based image retrieval, covering queries, representation, indexing, search, learning, and more * Face detection, alignment, and recognition--with new solutions for key challenges * Perceptual interfaces for integrating vision, speech, and haptic modalities * Development with the Open Source Computer Vision Library (OpenCV) * The new SAI framework and patterns for architecting computer vision applications-Easy to introduce the latest developments in computer vision. Include:* Camera calibration using 3D objects, 2D planes, 1D lines, and self-calibration* Extracting camera motion and scene structure from image s