搜索资源列表
fuc
- 破圈法,边割法,避圈法的比较: 当图为连通且边树较少时,用破圈法较好 当图边数较多时,使用边割法和避圈法较好 -breaking lap, cutting edge, avoiding the comparison circle : When map is connected and fewer side tree, breaking lap with a better method when the edges of a few more, the use of cut
tudeshengdubianli
- 图的深度遍历,用二叉树实现,输入时要遵循二叉树的顶点和边数的对应关系-traverse the depth map, using binary tree realize that the importation of binary tree to be followed when the number of vertices and edges of the relationship
dijkstraautomatique
- dijkstra算法,windows和linux下编译通过,可以从文件读取数据,也可以手动输入边数及点数,自动生成边长。-dijkstra algorithm, windows and linux under compile, can read data from the paper, can also manually input edges and points, automatic generation length.
Bellman_Fordautomatique
- bellmanford算法,windows和linux下编译通过,可以从文件读取数据,也可以手动输入边数及点数,自动生成边长。-bellmanford algorithm, windows and linux under compile, can read data from the paper, can also manually input edges and points, automatic generation length.
kthtree
- kthtree问题 给定一棵有向树T,树T 中每个顶点u都有一个权w(u);树的每条边(u,v)也都有一个 非负边长d(u,v)。有向树T的每个顶点u 可以看作客户,其服务需求量为w(u)。每条边(u,v)的边长d(u,v) 可以看作运输费用。如果在顶点u 处未设置服务机构,则将顶点u 处的服务需求沿有向树的边(u,v)转移到顶点v 处服务机构需付出的服务转移费用为w(u)*d(u,v)。 树根处已设置了服务机构,现在要在树T中增设k处服务机构,使得整棵树T 的服务转移费用最小-kt
2722
- 北京大学ACM题 Here is a geometric problem. You have an angle and some squares in the first quadrant of the plane rectangular coordinates. The vertex of the angle is fixed on the origin O of the coordinates, and both of its radial lines are specified
多种图像边缘检测与分割处理
- 程序代码说明 P0401:用Prewitt算子检测图像的边缘 P0402:用不同σ值的LoG算子检测图像的边缘 P0403:用Canny算子检测图像的边缘 P0404:图像的阈值分割 P0405:用水线阈值法分割图像 P0406:对矩阵进行四叉树分解 P0407:将图像分为文字和非文字的两个类别 P0408:形态学梯度检测二值图像的边缘 P0409:形态学实例——从PCB图像中删除所有电流线,仅保留芯片对象-code P0401 Note : Prewitt operator to detect
第四章 控制系统的分析方法
- 用Canny算子检测图像的边缘 P0404:图像的阈值分割 P0405:用水线阈值法分割图像 P0406:对矩阵进行四叉树分解 P0407:将图像分为文字和非文字的两个类别 P0408:形态学梯度检测二值图像的边缘 P0409:形态学实例——从PCB图像中删除所有电流线,仅保留芯片对象-with Canny operator to detect the edges in the image P0404 : image thresholding segmentation P0405 : water
第一章 计算机辅助设计与仿真技术概述
- 用Canny算子检测图像的边缘 P0404:图像的阈值分割 P0405:用水线阈值法分割图像 P0406:对矩阵进行四叉树分解 P0407:将图像分为文字和非文字的两个类别 P0408:形态学梯度检测二值图像的边缘 P0409:形态学实例——从PCB图像中删除所有电流线,仅保留芯片对象-with Canny operator to detect the edges in the image P0404 : image thresholding segmentation P0405 : water
图的遍历演示
- 一. 问题描述很多涉及图上操作的算法都是以图的遍历为基础的。试写一个程序,演示在连通的无向图上访问全部节点的操作。二. 基本要求以邻接多重链表为存储结构。实现连通无向图的深度和广度优先遍历。以用户指定的节点为起点,分别输出每种遍历下的节点访问序列和相应生成树的边集。-one. Descr iption many issues involving maps of algorithms are to traverse the map-based. A written test procedures,
Sea
- 用BP网络实现对图像的边缘进行提取,本程序为演示程序,可以看到BP在应用中的效果-BP network of image edges extraction, the procedure for the demonstration program, we can see BP in the application of the results
Imageprocessing.rar
- 包括图像分析的四部分代码:matlab扩散和高斯函数,线性扩散,线性复扩散,非线性扩散。,It contains four parts: [1]MATLAB function:diffusion.m gauss.m [2]Linear diffusion Applying linear diffusion to images creating linear scale-space. MATLAB code: demo_lin.m Image: haifa1.bmp [3]Li
shujujiegou
- 对任意给定的图(顶点数不小于20,边数不少于30,图的类型可以是有向图、无向图、有向网、无向网),能够输入图的顶点和边(或弧)的信息,并存储到相应存储结构(邻接矩阵、邻接表、十字链表、邻接多重表,任选其中两种类型),对自己所创建的图完成以下操作: -For any given map (not less than 20 vertices, edges not less than 30, the type of map can be a directed graph, undirected g
playMax
- 用回溯法和递归调用的思想实现了多边形游戏算法,用codeblocks开发。输入多边形的N个定点的数值和N条边的运算符,可计算任意断开一条边后计算所得的最大值。-Backtracking and recursive calls with the idea to achieve a polygon game algorithm, using codeblocks development. Input polygon fixed values of N and N edge
Dijkstra
- 这个例程,会在多条相同最短路径中选出边数最少的路径.只是改变path域即可在遍历的时候访问到边数少的路径.核心的思想,就是建立一个数组,存放从出发点到当前顶点的最短路径边数.通过每次查看最短路径相同的情况, 即dv + cvw = dw.时,如果 Count[v] + 1 < Count[w]时,就执行 Count[w] = Count[v] + 1, 同时 w -> path = c.-This routine will be the same number of shortest
residues
- 该文件含残差点数目计算、均方差计算、信噪比计算、边缘等效视数计算-The document containing terms of the number of residues are calculated variance, SNR calculation, calculation of equivalent number of edges
Acquisition_canny
- Matlab code to acquire a frame from video input device and find edges using canny algorithm
regionbased_seg
- The wellknown ChanVese segmentation algorithm from the paper “Active Contours Without Edges,” is a great example of active contours
wavelet-edges
- edges detection using wavelet tansform
projection-functions-in-mouth-detection-edges
- In this source code we used integral and variance projection functions and their gradients to find mouth edges.