bpsko_analysis

本程序是多结构元素形态学滤波的探讨，通过选择不同的结构元素多尺度序列Bi，来得到最合适的结果(This program is a multi-structure elements of morphological filtering by selecting different multi-scale structure elements sequence Bi, get the most appropriate results)

说明：  相关图像算法包括大律法分割，梯度分割，分水岭分割，活动轮廓，最小生成树，相关基因算法(Great Law Segmentation, Gradient Segmentation, Watershed Segmentation, Active Contour, Minimum Spanning Tree, Related Gene Algorithms)

我写的贝叶斯fusion的Visual C+++源码，简明易懂，提供参数说明 可直接使用。 (The Bayesian fusion the Visual C+++ of what I wrote source, easy-to-understand parameters can be used directly.)

利用霍夫线检测实现车道线的自动检测并判断是否偏离(Using Hof line detection to achieve automatic detection of lane line and determine whether or not to deviate the)

说明：  基于图像灰度的图像拼接。由两幅内容有重叠的图像拼接成一幅视野更大的图像。(Image mosaic based on image gray scale. Content from the two overlapping images together into a larger image view.)

边缘检测，并分割，以不同颜色标示。站内有其matlab实现，这是对应的c++代码。(Edge detection and segmentation, marked with different colors. Inside the station are the matlab realize, This is corresponding c++ code.)

otsu算法实现，可以自适应获取阈值，对图像进行二值化。里面面配有图像均衡化的程序一起使用，效果更好， (otsu algorithm adaptive obtain the threshold image binarization. Inside surface with image equalization program used together, the better)

EDLines是一种快速直线检测算子，2012年在ICCV上提出，也是目前处理直线检测最快的算法之一，该算法包含三个步骤：（1）边缘提取：利用Edge Drawing (ED)算法[28,29]从灰度图像中提取边缘片段；（2）线段检测：利用最小二乘法提取直线段；（3）线段确认：遵循Helmholtz定律，从已提取的直线段中摒弃虚假线段。EDLines算法的优越性得益于Edge Drawing (ED)算法能够从灰度图像中准确、快速、稳定地提取出光滑、完整的边缘片段。Edge Drawing (ED)算法包含以下步骤： （1）采用size=5*5,σ=1的高斯核对灰度图像进行平滑滤波，去除噪声； （2）采用一种常用的梯度算子，如Prewitt、Sobel或Scharr等计算平滑后图像中每个像素点的梯度幅度和梯度方向； （3）将梯度图中邻域内幅度最大的像素点标记为锚点，这些锚点成为图像边缘点(edge elements)的概率很大； （4）将相邻的锚点连接成边缘线。从一个锚点起始，ED利用相邻像素的梯度幅度和方向在梯度为最大值的锚点之间游走。 (Edge Drawing (ED) is our recently-proposed, novel, fast edge detection algorithm. What makes ED stand out the existing edge detectors, e.g., Canny, is the following: While the other edge detectors give out a binary edge image as output, where the etected edge pixels are usually independent, discontinuous entities ED produces a set of edge segments, which are clean, contiguous, i.e., connected, chains of edge pixels. Thus, while the output of the other edge detectors requires urther processing to generate potential object boundaries, which may not even be possible or result in inaccuracies ED not only produces perfectly connected object boundaries by default, but it also achieves this in blazing speed compared to other edge detector.)

dib图像的读取，显示以及存储，能够运行(dib image read, display, and storage, and be able to run)

基于纹理分析的图像分割，matlab开发，用entropyfilt，stdfilt等(Image segmentation based on texture analysis, matlab development, with entropyfilt, stdfilt etc.)