attack

一种快速图像阈值分割法，不是otsu或迭代法，Wellner 1993快速自适应的图像二值化方法，有具体使用方法，很详细(A fast image thresholding segmentation method, not otsu or iterative methods, Wellner 1993 fast adaptive image binarization method)

基于侧抑制的图像分割，在ＰＣＮＮ分割的基础上实现(failed to translate)

图形图像处理算法大全，包含各种算法的源码，只要经过简单修改就可变为程序(Daquan graphic image processing algorithms, including the source code for various algorithms, as long as you can into a program after a simple modification )

检测鼠标信息，C++Builder精选编程学习源码，很好的参考资料。(Detecting mouse information, C++Builder select learning programming source code, a good reference.)

本算法有图像融合算法，聚类分析算法，去噪算法，运动模糊算法(This algorithm with image fusion algorithm, clustering analysis algorithm, the denoising algorithm, fuzzy algorithm)

IDL编写的以时间为变量的散点图代码,值得新手学习(IDL prepared time-variable scatter plot code, novice worth learning)

用IDl编写的，用IDL图像处理。已调试好的程序。(Prepared using IDL with IDL image processing. Debugging process has been good.)

是图像处理中常用的测试图库，非常实用,如lena图片， 青椒图片，以及zelda图片等(is the test pictures used in image processing very useful)

提出了一种针对复杂环境下的过人脸检测方法，首先在CbCgCr空间利用直接最小二乘法构建了对光照和复杂背景鲁棒性更好肤色聚类模型，实现了准确的肤色检测；然后针对人脸中姿态和表情变化，提出了基于Adaboost的多姿态人脸检测，精确的实现了人脸检测定位。(Extraordinary face detection method for complex environments, the first space CbCgCr ​ ​ direct least squares method to build a better robustness to light and complex background color clustering model to achieve accurate color detection forface, posture and facial expression changes, proposed the multi-pose face detection based on Adaboost, accurate face detection and location. )

卡尔曼滤波源代码 Some brief notes ---------------- kfdemo.m is a Matlab script file to run a demonstration of the Bayesian Kalman filter. It loads file kfdemo.mat (saved as version 4 so that it will read in either v4 or v5 Matlab). The other files are called by kf.m (the Kalman filter) or included as they may be useful. Normalis.m normalises data to zero-mean, unit variance along components. I always do this before any further analysis. Steve Roberts 7-2-98 (Kalman filter source code Some brief notes kfdemo.m is a Matlab script file to run a demonstration of theBayesian Kalman filter. It loads file kfdemo.mat (saved as version 4so that it will read in either v4 or v5 Matlab). The other files are called by kf.m (the Kalman filter) or includedas they may be useful. Normalis.m normalises data to zero-mean, unit variance along components. I always do this before any furtheranalysis.Steve Roberts 7-2-98)