source_code_TBM_activecontours.tar

基于小波和形态学的自然地面背景红外目标检测方法。。。。。。(Based on wavelet and morphology of the natural terrestrial background infrared target detection method)

摄影测量源码，连续法的相对定向算法，提供实验数据和程序(Photogrammetric source, the relative orientation algorithm of the continuous method, the experimental data and procedures)

矩形检测：用霍夫直线检测方法来对图像中的矩形进行检测。开发环境：vc6，需要安装OpenCV。OpenCV只是用来读取和显示图像等简单操作。(Rectangle detection: Hough line detection method using the image of the rectangle to test. Development Environment: vc6, need to install OpenCV. OpenCV is used to read and display images such as simple operation.)

I WANT SOURCE CODE FOR IMAGE SEGMENTATION

对全极化数据进行多视处理,针对T矩阵，C语言编写。(Multi-look of PolSAR)

针对图像秘密共享前需要像素置乱的问题，基于(t, n)门限多重秘密共享思想，提出一种免置乱的图像秘密共享方案，以第n+1人的秘密份额作为因子参与秘密分割与重构，加大相邻像素之间的差距(Based on (t, n) threshold multiple secret sharing ideas, and put forward a kind of scrambling image from secret sharing scheme to n+ 1 people share the secret as factors involved in secret segmentation and reconstruction, increase the gap between adjacent pixels)

本代码可以实现图像的维纳滤波，经过调试无错误，对于学习图像处理有较好帮助。(This code can achieve the image filtering, error-free through the debugging, better for learning image processing help.)

讨论了OpenCV(Open Source Computer Vision Library)相对于现有的计算机视觉软件包所具有的优势，描述了OpenCV的 环境配置、数据定义、图像元素访问方式。OpenCV成为一种源码开放、包含丰富的高级数学计算函数、图像处理函数和计算机视觉 函数、不断更新和平台无关性的计算机视觉软件包。(Discussed the OpenCV (Open Source Computer Vision Library) relative to the existing computer vision, the advantages of packages, description of OpenCV environment configuration, data definition, the image element access mode. OpenCV become an open-source, contains a wealth of advanced mathematical calculations, functions, image processing functions, and computer vision functions, continuously updated, and platform-independent package of computer vision.)

数字图像处理 opencv 一些基本例子和源码(opencv code)

对两幅图像进行配准，分别提取两幅图像的surf特征点以及描述子，得到粗匹配结果，然后根据粗匹配结果，采用ransac方法计算基础矩阵，并去除误匹配点，得到较准确匹配结果(Two image registration, surf was extracted from the feature points in two images to get the coarse matching and descriptor, then according to the results, the coarse matching results, using RANSAC method to calculate the fundamental matrix, and eliminate the error matching, gain a more accurate matching results)