The Core Library (PCL) is a powerful, cross

基于Fisher适应函数的遗传算法来做图像分割-Fisher-based fitness function of genetic algorithm to do image segmentation

数字图象处理 VC++源代码，包含图象读取、点运算。区域运算、分析、识别 -digital image processing VC source code contains images read, point computation. Regional operations, analysis, identification

该RAR包含了指纹识别的相关资料，以及发展趋势，和参考方案-The RAR contains the fingerprint of the relevant information, as well as the development trends, and reference programs

该源代码可以实现实时的3D效果处理，而且使用非常方便、快速，对很多的视频，图像等文件格式都兼容。-the source code can achieve real-time 3D effects, but also extremely easy to use, fast, a lot of video, images, etc. are compatible file format.

长40页的word中文文档: 通过本篇文章能对Java的初学者提供帮助,弄清一些Java编程技巧,如事件,线程,动画,双缓冲图像,复合键控制,等.一方面有助于Java编程学习,另一方面即使使用C或C++编程,本文的算法和技巧也都有相当价值.-the 40-word Chinese Document : This article can be Java beginners to help clarify some of the Java programming techniques such as incident, thread, animation, image-buffer, composite bonding control, and others. Both help to learn Java programming, and even if the use of C or C programming, the paper algorithms and techniques also have considerable value.

绘制给定数据的波形，跟上次传的那个一样，就是一个CGraph 类，主要是改进了一点算法，修正了一点错误-drawn to the waveform data set, with the last word that the same, which is a CGraph category, the main point is to improve the algorithm, amended 1:00 wrong. .

vega中的tripod碰撞检测方法，上房问题在min和Max的参数中。如果max值越大，你爬高就越大。min越小你下坡也就越大。他们的值与你的场景单位有关。他们都是极限值，如果你的房子高度在max值之下就不可能“上房”了。你的坡度落差大于min的绝对值时，他就下不去了。一般用在z和Tripod中常见-vega in the tripod of collision detection methods,上房problem min and Max parameters. If the max value bigger, you climb the greater. min greater the smaller the downhill you. Their value and your scene units. They are limits, if your house under a high in the max value can not be

完整的图文排版打印源程序,通过演示打印输出简历,集中演示了图象排版打印技术。-integrity typesetting Print copies of the source, through the demonstration of Print output resume, a demo concentrated Print Image typesetting technology.

该算法用帧间差分法将帧中的背景象素点检测出来,再确立出背景帧;由于排除了帧中运动物体的影响,因而提取出的背景干净,效果很好,然后运用背景差分检测出场景中的物体，结果表明,该方法快速有效,能够满足实时性的要求

应用背景机器视觉中，图像处理算法很多，但是大都处理复杂，我看了大量算法提取出一套比较简单有效的跟踪算法。基于opencv库函数对图像的强大处理能力和卡尔曼滤波原理的精妙，算法效果明显。欢迎大家借鉴使用，有意机器视觉学习的朋友欢迎提出建议。关键技术主要是利用opencv对图像的处理，灰度化，二值化，然后进行轮廓识别加上方框标记，最后利用卡尔曼滤波跟踪。关键思路是对提取出的多个轮廓进行最大值选取，从而确定跟踪点，为卡尔曼滤波的使用提供接口。为防止找不到最大轮廓的bug还设计了一个小算法。