OpenTiff

在HSV色彩空间进行彩色图像分割源码，包括学习和训练算法，获得分割参数(In the HSV color space for color image segmentation source code, including learning and training algorithm, access to segmentation parameters)

通过对彩色图像的处理，来计算某一个区域的面积。(The color image processing to calculate the area of ​ ​ a region.)

该数字图像处理文件有很强的修改能力，可以仔细的分析每一个频域不同条件下的实验结果分析。有很强的处理图像能力(The digital image processing of documents has a strong ability to change and be more careful analysis of each under different conditions, a frequency-domain analysis of the experimental results. Has a strong ability to deal with images)

基于SIFT的图像配准程序 SIFT特征匹配算法是目前国内外特征点匹配研究领域的热点与难点,其匹配能力较强,可以处理两幅图像之间发生平移、旋转、仿射变换情况下的匹配问题,甚至在某种程度上对任意角度拍摄的图像也具备较为稳定的特征匹配能力(Hot and difficult of the current research areas of domestic and foreign feature point matching based the SIFT image registration program SIFT feature matching algorithm is its ability to match between the two images, can handle translation, rotation, affine transformation case match problem, even in some degree images taken at any angle with more stable feature matching ability)

对两帧图像进行ICM调试.包含内容：1估计姿态和摄像机内参数；2两幅图做四次金字塔；3利用输入特征点采用ransac算法估计姿态R, T。4sift特征匹配；5摄像机标定。(ICM images on two debugging. Contains: 1 Estimated posture and intrinsic parameters 2 two plans to do four pyramids 3 using the input feature points using ransac algorithm estimates gesture R, T. 4sift feature matching 5 camera calibration.)

说明：  MATLAB开发接收串口数据并实时将其转化为图形显示(MATLAB Develops and Receives Serial Port Data and Converts it into Graphic Display in Real Time)

此程序可以帮助您管理以及排版您的图片集，效果美观(This program helps you to manage and typeset your photo collections with beautiful results)

基于稀疏编码和线性塔式匹配的图像分类算法。(This package contains the Matlab codes implementing the ScSPM algorithm described in CVPR 09 paper "Linear Spatial Pyramid Matching using Sparse Coding for Image Classification". )

说明：  对图像目标识别和提取，主要通过改进非线性阈值分割实现(For image target recognition and extraction, the main method is to improve the non-linear threshold segmentation.)

提取图像的lbp纹理特征，然后进行向量表示( Lbp extracted texture features of the image, and then vector representation)