图像处理：旋转、平滑、轮廓、模糊、亮度调节等等处理

该程序为一维离散小波变换的matlab程序，很实用-The procedure for the one-dimensional discrete wavelet transform matlab program, it is practical

一篇很多人找的经典图像处理算法方面的文章。-a lot of people find the classical image processing algorithm articles on the subject.

算术编码的c语言源代码实现，写的不好，希望大家提提意见-arithmetic coding in C language source code to achieve and write well, you make a suggestion hope

mean shift 均值漂移算法的matlab实现，大家可以看看，比较实用-mean shift algorithm matlab mean-shift realize, we can look at more practical

利用K均值聚类的方法实现人体的检测，混合高斯模型建立背景并实时更新-The use of K-means clustering method to achieve the human body detection, Gaussian mixture model to establish the background and real-time updates

转换图象为二值图象后，进行识别与标记的matlab源码。可以计算目标物个数，形心等。-image conversion value for the two images, identification and marking of Matlab source. Can be calculated from the number of goals, such as heart-shaped.

使用OPENCV进行运动目标跟踪，在Visual C++ 2005 环境中使用新算法实现多运动目标的跟踪和检测。-this is a object motion tracking system with Visual c++ 2005 and opencv。it can process successly check and track multi-objects。

robustly fits a fundamental matrix to a set of putatively matched image points. This function uses an 8 point fundamental matrix solution-robustly fits a fundamental matrix to a set of putatively matched image points. This funct ion uses an eight point fundamental solution matrix

：由于许多传统的去噪方法在强背景噪声情况下提取声音信号的能力变弱甚至失效， 提出 应用独立成分分析( I C A) 方法对声音信号进行特征提取， 并证明了这种 I C A 变换能增强语音和音 乐信号的超高斯性． 在此基础上， 应用 I C A基函数作为滤波器， 通过阈值化的去噪方法对含有强高 斯背景噪声的声音信号进行去噪仿真实验． 结果表明， 本方法明显优于传统的均值滤波和小波去噪 方法， 为强背景噪声下弱信号的检测提供 了新的途径．-: As many of the traditional de-noising method in case of strong background noise, the ability to extract the voice signal even weaker failure, the application of independent component analysis (ICA) method of voice signal feature extraction, and prove that this transformation can be enhanced voice ICA and music of super-Gaussian signals. On this basis, the application of ICA basis function as a filter, through the threshold of the denoising method of Gaussian background noise contains strong voice signal denoising simulation. The results show that this method is obviously superior to the traditional mean filtering and wavelet denoising methods for the strong background noise under the weak signal detection provides a new way.

用DELPHI实现的验证码识别的最基础例子!-DELPHI realize with the Verification Code to identify the most basic examples!