LBP

立体视觉代码。主要过程包括：harris角点检测，zncc最优策略匹配，扩散得到更多特征对应，计算disparity和对应颜色值。另外提供了两幅图片以及对应的特征匹配的结果和disparity图像。(Three-dimensional visual codes. The main process includes: harris corner detection, zncc optimal strategy for matching, the proliferation of more features of the corresponding calculation of disparity and the corresponding color value. Also provides a picture and two corresponding feature matching results and disparity images.)

基于马尔可夫随机场（MRF）的图像分割算法(Image segmentation algorithm based on Markov Random Field (MRF))

这是一个利用导数光谱分析的方法检测特征吸收波段的源代码，可供从事高光谱图像处理的朋友分享。(This is a use of derivative spectroscopy method of the characteristic absorption band of the source code, available to engage in high-spectral image processing share.)

图像细化处理的C代码，效果较好，对初学者有较好的参考作用(Image processing of C code, the effect is good, is good for beginners reference)

可根据需要自定义窗口形状，用于各种特效窗口开发(Customizable window shape, for a variety of special effects needed to develop window)

matlab编写的harris程序,对初学者还是很有帮助的(harris program written in matlab, or helpful for beginners)

SVM算法的线性分类，图像分类单幅遥感图像特征提取分类(Linear classification of SVM algorithm, image classification, feature extraction and classification of single remote sensing image)

纯C实现的 图像处理开运算，对bmp格式(Pure C implementation of image processing open operation on bmp format)

用matlab实现人眼定位的程序 ，包括滤波、阈值分割、人眼粗定位、精确定位等。(Using matlab realize the human eye positioning procedures, including filtering, threshold segmentation, the human eye coarse positioning, precise positioning.)

本文主要研究基于水平集方法的活动轮廓模型图像分割，在回顾活动轮廓模 型发展的基础上，介绍了曲线演化理论及其水平集方法，证明了水平集方法可以 有稳定的数值实现方式且其处理拓扑变化的自然性，进一步引出了变分水平集方 法。 本文介绍了两种不同的几何活动轮廓模型：基于梯度信息的李纯明模型以及 基于区域信息的 Chan-Vese 模型（C-V 模型）。在分析上述两模型的优缺点上，提 出了一种改进的 C-V 模型，改进模型引入了距离约束项，同时对基于区域的外部 能量项进行了改进，使得水平集函数重新初始化寓于模型的演化之中，分割结果 对参数的依赖性减小。 (This paper mainly study image segmentation of active contour model based on level set. After reviewing the development of the active contour model, curve evolution and level set method are presented, then we proved that the level set method has a stable numerical realization and can describe the topology change of the contour naturally, in addition we introduce level set of variational method. We introduce two different GAC models in this paper: Li Chunming model which is based on gradient information and Chan-Vese model （C-V model） which is based on region information. Based on the drawbacks and advantages of these two models, we improve the C-V model by adding penalizing energy term of signed distance function, at the same time, mending the external energy term which based on region information, then the re-initialization of the level set can accomplish in the model evolution, and the degree of the segmentation result depend on the parameters decline. )