retinex.opencv

这个实例就像一个魔镜一样，能把原始图像照出各种变换效果,是基于MFC的多文档应用程序(This example is like a mirror,which can convert original image according to a variety of effects)

利用opencv工具包的图像缩小程序利用opencv工具包的图像缩小程序利用opencv工具包的图像缩小程序(image shrink with opencv image shrink with opencv image shrink with opencv)

VC中绘制坐标系、网格、常用数学函数以及辅助功能（背景色切换、坐标标题修改等）(vc draw)

本人开发的火焰识别程序，包括otsu自适应阈值，canny边缘检测，形态学膨胀、腐蚀操作，尖角判别，圆形度计算。在vc下编译通过。(development of the flame identification procedures, including otsu adaptive threshold, canny edge detection, Morphological expansion, corrosion operation, pointed discriminant, circular calculation. Under the vc compile.)

指纹识别demo 演示方向图、roc曲线(fingerprint demo show orientation and ROC curve)

数字图像处理编程入门（吕风军）第一章第1章 Windows位图和调色板(Windows Bitmap and palette of the first chapter, Chapter 1 of the digital image processing program entry (Lv Fengjun))

视频演示算法包括： 1. 静态背景下的背景预测法目标检测 2. 静态背景下帧间差分法目标检测 3. Mean Shift目标跟踪方法 4. 重心多目标跟踪方法 (Algorithm for video presentation include: 1. Static background background prediction target detection 2. Static background frame difference method for target detection 3. Mean Shift tracking method 4. Gravity multi-target tracking method)

自主选择性的查看一幅图像中的部分区域的颜色直方图：允许用户在一幅图像中选择一个矩形区域，通过按住鼠标键画一个矩形，当鼠标放开是，高亮显示矩形框，同时在另一个独立的窗口中，使用画图函数画一个图表（选定区域的颜色直方图），分别用蓝，绿，红表示选中区域中每种颜色的像素数量。(Self-selective color in an image to view a partial area of ​ ​ the histogram: Allows the user to select a rectangular area in an image by holding down the mouse button to draw a rectangle when the mouse is released, the highlighted rectangle, Meanwhile in a separate window, using the drawing functions to draw a chart (selected color histogram region), respectively, with blue, green, red indicates the number of pixels in the selected area of ​ ​ each color.)

opencv SIFT源码详细分析，代码能够准确实现(opencv SIFT detailed analysis of the source code can achieve accurate)

三维激光点云配准是点云三维建模的关键问题之一。经典的 ICP 算法对点云初始位置要求较高且配准 效率较低，提出了一种改进的 ICP 点云配准算法。该算法首先利用主成分分析法实现点云的初始配准，获得较好 的点云初始位置，然后在经典 ICP 算法的基础上，采用 k － d tree 结构实现加速搜索，并利用方向向量夹角阈值去除 错误点对，提高算法的效率。实验表明，本算法流程在保证配准精度的前提下，显著提高了配准效率。 (Three-dimensional laser point cloud registration is one of the key three-dimensional point cloud model. High classical ICP algorithm to the initial position of the point cloud registration requirements and low efficiency, proposed an improved ICP point cloud registration algorithm. Firstly, the use of principal component analysis of the initial point cloud registration, get a better initial position of the point cloud, then the basis of classical ICP algorithm using k- d tree structure to achieve speed up the search, and using the direction vector angle the removal of the threshold point error and improve the efficiency of the algorithm. Experiments show that the algorithm processes to ensure the accuracy of registration under the premise, significantly improve the efficiency of registration.)