pca

说明：  多阈值的OTSU算法，用于对图像的分割。matlab语言编写。(Otsu algorithm with multiple thresholds for image segmentation)

主成分分析算法（PCA），可用于降维，也可用于处理图像相关性问题，提取主成分，分析图像细节信息和主要成分，用于图像压缩也可以(Principal component analysis algorithm (PCA), can be used for dimensionality reduction, can also be used to process images related issues, extracted principal component analysis and main component of image detail information, to be used for image compression)

说明：  图像处理，图像分割，图像变换，图像特征提取，图像增强，图像编码压缩(Image processing, image segmentation, image transformation, feature extraction)

基本图元绘制、计算机图形学上机实验报告、1，熟悉图形软件开发工具：VC++, OpenGL等； 2，设计、实现线段的DDA、Bresenham算法 3，设计、实现中点圆、中点椭圆生成算法； 4，设计、实现填充图元生成算法；(The basic primitive computer graphics, computer lab report 1, familiar with the graphics software development tools: vc++, OpenGL, etc. 2, design implementation DDA Bresenham algorithm of line 3, midpoint circle midpoint elliptical generation algorithm design implementation 4, primitive design to realize filling generation algorithm)

利用最小二乘法，可以自动实现图像中的椭圆检测并拟合出来，效果很好(Ellipse detection and fitting them to achieve)

超分辨率复原（分块处理） 将样本库中的高分辨率图象和低分辨率图象分别做分块处理，当新输入一幅低分辨率图象时，分成小块到样本库中寻找最匹配的高分辨率块，然后复原出高分辨率图象。(Superresolution recovery (block processing) for a sample of high-resolution images and low-resolution images respectively block , when the new importation of a low-resolution image, divided into small samples to find the most matching high-resolution block, then recovery from high-resolution images.)

简单的图像积分图的汇编算法；图像积分图的计算在图像处理中经常用到(A simple compilation of the image points map algorithm image points in the map frequently used for image processing)

题目： 八宝粥的生产过程中需要用到大量的红豆（红蚕豆），而实际上从红豆产地购买得到的红豆中会参杂一些杂物和不合格红豆。为了保证八宝粥的质量，需要对红豆进行筛选，去除不合格红豆和其它杂物。目前国内在红豆筛选工序上仍然使用人工筛选的方式，存在人工成本高、精确度差、劳动强度大等缺点。因此八宝粥生产厂商迫切需求开发一款能够自动实现红豆筛选的自动化筛选机。针对上述需求，请设计筛选机中的基于可见光图像的红豆筛选算法，该算法应尽可能的准确的找到参杂在红豆原料中的不合格红豆和杂物。 附件包括两个不同实验环境下拍摄得到的红豆相关图片样本库，实验环境分别为自然光照条件和灯光条件。每个条件下的样本库包括合格、不合格、杂物和混合四类样本的图像，其中合格、不合格以及杂物的图像可用来训练或建模，混合类图像用来测试算法的准确性和实时性。同学可在自然光照环境下的样本库或者灯光条件下的样本库中任选其一，用于解决上述问题。 作业提交格式包括以下四个内容： 一、 问题分析 二、 算法设计 三、 实验结果(将自己选择的样本库中的混合样本图片中的样本个体进行分类，并给出可视化的分类结果。) (Title:Use a lot of red bean production process of eight-treasure porridge ( red bean ), but in fact from the Red areas available in red bean can blend some sundries and unqualified red bean. In order to ensure the quality of eight-treasure porridge, the need for screening of red bean, red bean and other debris removal is not qualified. At present in the domestic bean screening process still use manual screening method, has the disadvantages of high labor costs, poor accuracy, high labor intensity. Therefore, eight-treasure porridge manufacturers need to develop a can achieve automatic bean screening automatic screening machine. According to the above requirements, please design screening machine selection algorithm based on visible light image of the red, the algorithm should be as accurate as possible to find the mixed in the bean raw materials in the unqualified red bean and debris.Accessories include captured in two different experimental environment of the red bean image sample dat)

发表于ECCV上的一篇用于人脸识别的算法，Gabor Feature based Sparse Representation for Face Recognition with Gabor Occlusion Dictionary (At ECCV on an algorithm for face recognition, Gabor Feature based Sparse Representation for Face Recognition with Gabor Occlusion Dictionary)

暗原色先验的视频去雾算法 matlab实现(the code of defog using dark-chanel prior algorithm)