work

本人搜集的Ostu图像二值化的算法，是在MATLAB环境下写的，不过上传的代码是文本格式的，各位可以根据自己需要参照一下(I collect images of two gray value of the algorithm is to write MATLAB environment, But the code is uploaded to the text format, you may need to refer to themselves)

[Wang 1998]Spiral CT Image Deblurring for Cochlear Implantation

静态图片转化为动态图片，把静态的图片转化为动态的(convert PNG picture to GIF picture)

java 图形算法实现源代码，有坐标放大缩小。(java graphics algorithm source code, coordinates Zooming.)

实现了图像的加水印，去噪，加噪声等功能，基于kaiser窗的双谱线插值FFT谐波分析，用于建立主成分分析模型。( Realize image watermarking, de-noising, plus noise and other functions, Dual-line interpolation FFT harmonic analysis kaiser windows, Principal component analysis model for establishing.)

实现了对10个数字音的识别，是学习PCA特征提取的很好的学习资料，包括调制，解调，信噪比计算。( To achieve the recognition of 10 digital sound, Is a good learning materials to learn PCA feature extraction, Includes the modulation, demodulation, signal to noise ratio calculation.)

Visual C++数字图像处理技术与工程案例，各章节源代码，这是第一章的代码(The Visual C++ digital image processing technology and engineering cases, the source code of each chapter, this is the first chapter of the code)

对图形的旋转 有不错的效果 可以试试 让图形从左到右(Rotation pattern has a good effect can try)

用分水岭算法对三维模型进行分割处理。可以实现对三维模型的有意义分割。(Using three-dimensional model of the watershed algorithm to be dealt with separately. Three-dimensional model can achieve meaningful partition.)

说明：  本文以k-means算法为背景，引入信息熵相关知识，从而实现全自动分割图像。然而在利用混合高斯模型对图像进行数据分析时，会发生一定的过拟合现象，导致我们得不到预期的聚类数目。本文设计合理的合并准则，令模型简化，有效地消除过拟合现象，使得最后得到的聚类数目与预期符合。，设计合理的准则改进了图像的全自动分割方法，使得分割结果更加优化(In this paper, k-means algorithm is used as the background, and information entropy related knowledge is introduced to realize full-automatic image segmentation. However, when the Gaussian mixture model is used to analyze the image data, there will be some over-fitting phenomenon, resulting in that we cannot get the expected number of clusters. In this paper, a reasonable merging criterion is designed to simplify the model and effectively eliminate the over-fitting phenomenon, so that the final clustering number is in line with the expectation. A reasonable criterion is designed to improve the automatic image segmentation method and make the segmentation result more optimized.)