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这是图像处理中HSV课件颜色特征提取（将H5等份，S,V分量各三等份）MATLAB源码。(This is the image processing in HSV color feature extraction software (to be H5 equal, S, V component of the third class) MATLAB source.)

说明：  本压缩包主要包括数字图像处理——使用MATLAB分析与实现的源代码(This compression package mainly includes digital image processing - using MATLAB analysis and implementation of the source code)

说明：  基于Kmeans算法的图像分割，一般Kmeans是数据挖掘中用来聚类的，本试验利用图像中的灰度值作为Kmeans算法的原始点，进行图像分割(Kmeans algorithm based on image segmentation, data mining in general Kmeans is used to clustering, the trial use of the image gray value as the original algorithm Kmeans spots for Image Segmentation)

一种利用中心和结构聚类的稀疏表示图像去噪方法，有不错的效果(a image denoising method with structral clustering and sparse representation, has good effect .)

对图像进行滤波，顶帽变换并计算中心，有图片，可直接运行。(The image filtering, top-hat transform and Computing Center, there are images which can be directly run.)

本文首先概述了独立成分分析与盲信号分离， 主成分分析的关系， 然后系统地介绍了该技术的基本概念和数据模型， 对现今比较流行的各种独立成分分析算法进行了剖析和总结。最后对独立成分分析的发展及应用前景作了展望(In this paper, an overview of independent component analysis and blind signal separation, principal component analysis of the relationship, and then systematically introduces the basic concept of the technology and data models for today' s more popular variety of independent component analysis algorithm is analyzed and summarized. Finally, independent component analysis of the development and application prospects are described)

说明：  基于FPGA平台的双目视觉处理项目，可以通过双目摄像头实现目标物体测距，测量大小等功能(Binocular vision processing based on FPGA platform)

FCM源代码，专门用于图像分割的，速度很快(FCM source code, specifically for image segmentation, very fast)

DCT1.m为一维离散余弦变换exp22.m为对一幅灰度图像进行离散余弦变换 exp23.m为对一幅彩色图像进行离散余弦变换(DCT1.m for the one-dimensional discrete cosine transform exp22.m for a gray image exp23.m discrete cosine transform for the color of an image discrete cosine transform)

SURF算法作为一种新近出现的特征提取方法，在重复度、独特性、鲁棒性3个方面，均超越或接近以往提出的同类方法，并在计算效率上具有明显的优势。本代码采用SURF算法检测图像并进行坐标变换与图像拼接。 采用SURF算法对图像进行检测，其主要是用Hessian矩阵对图像进行检测，对图像的特征提取之后找到图像的特征点。之后采用最近临快速匹配（NN）、随机抽样一致性（RANSAC）算法和最小二乘法参数优化（LM）对特征点进行提纯匹配。最后在两幅图像中进行坐标变换，达到统一坐标系和图像拼接的效果。 (SURF（Speeded Up Robust Features） as a method of feature extraction which newly appeared is over or nearly previous method on duplication, uniqueness, and robustness and have a clear advantage on computational efficiency. This code uses the SURF and coordinate transformation algorithm to detect image and image matching. This code uses the SURF algorithm of image detection, the main is to use the Hessian matrix of image for testing, to find the image after image feature extraction of feature points. After we used Nearest Neighbor (NN), Random Sample Consensus (RANSAC) algorithm and least square parameter optimization for purification of matching feature points. Coordinate transformation in the last two images, to coordinate system to achieve the same image stitching. )