acc的matlab代码在图像霍夫变换中找到线和圆此处的代码文件对图像中的直线和圆执行霍夫变换。hough_lines_acchough_peaks模仿了matlab内置函数hough和hougpeaks。它们具有相同的输入和输出参数。
tmpInImage_Y = YCbCr(:,:,1); 1. tmpInImage_Cb = YCbCr(:,:,2); 1. leftC = int32(zeros(rH,1)); 1. rightC = int32(zeros(rH,1)); 1. Rs = int32(zeros(rH,1)); 1. twoLines_1b = twoLines_0b([2 1 4 3], :); 1. for i=oneI32:int32(length(twoLines_1b(:)))...
find 查找非零元素的下标 附录3 语言结构与调试 附录3.1编程语言 函数名 功能描述 函数名 功能描述 builtin 执行Matlab内建的函数 global 定义全局变量 eval 执行Matlab语句构成的字符串 nargchk 函数输入输出参数个数检验 feval 执行字符串指定的文件 script Matlab语句及文件信息 function Matlab函数定义关键词 附录3.2...
代码如下：——复制即可。function applyhatch(h,patterns,colorlist) %APPLYHATCH Apply hatched patterns to a figure %APPLYHATCH(H,PATTERNS) creates a new figure from the figure H by %replacing distinct colors in H with the black and white %patterns in PATTERNS. The format for PATTERNS can be %a...
1 링크 번역 답변:Swarooph2016년 10월 19일 I have an image which contains canny output of it. now, I want to find diagonal line that exist in top left part of image. do you have any idea? 카테고리 Image Processing and Computer VisionImage Processing ToolboxImage...
%Hough.lines Find lines % %L = HT.lines() is a vector of LineFeature objects that %represent the dominant lines in the Hough accumulator. % %L = HT.lines(N) as above but returns no more than N LineFeature %objects. % %Lines are the coordinates of peaks in the Hough accumulator. ...
row4 = find(binaryImage(:, end), 1, 'end'); % Seal edges binaryImage(:, 1) = true; binaryImage(:, end) = true; % Fill in the line. binaryImage = imfill(binaryImage, 'holes'); % Erase temporary lines on edges that we made. binaryImage(:, 1) = false; binaryImage(:, end...
line 创建线对象,lines 采用plot 画线色linmod 获连续系统的线性化模型linmod2 获连续系统的线性化精良模型linspace 线性等分向量ln 矩阵自然对数load 从MAT文件读取变量log 自然对数 log10 常用对数log2 底为2的对数loglog 双对数刻度图形logm 矩阵对数logspace 对数分度向量...
line 创建线对象 lines 采用plot 画线色 linmod 获连续系统的线性化模型 linmod2 获连续系统的线性化精良模型 linspace 线性等分向量 ln 矩阵自然对数 load 从MAT文件读取变量 log 自然对数 log10 常用对数 log2 底为2的对数 loglog 双对数刻度图形 logm 矩阵对数 logspace 对数分度向量 ...
image./max(max(globsegimage))); figure(1), imshow(label2rgb(globsegimage, 'gray')); title('Segments'); % Calculate boundary of segments BW = edge(globsegimage,'sobel', 0); % Superimpose boundary on original image iout = img; if (depth == 1) % Gray image, so use color lines ...