代码搜索：hough 开发教程
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m hough_circle.m
function [hough_space,hough_circle,para] = hough_circle(BW,step_r,step_angle,r_min,r_max,p)
% %%%%%%%%%%%%%%%%%%%%%%%%%%
% input
% BW:二值图像；
% step_r:检测的圆半径步长
% step_angle:角度步长，单位为弧度
% r_min:最小
www.eeworm.com/read/366483/9812031
m hough_simu.m
%%%%在无噪声情况下,和噪声为6DB的情况下%%%%%%%%%%
%%%%利用Hough变换检测运动轨迹为直线的目标%%%%%%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
close all;clear all;clc;
a=zeros(128,128);
for i=1:64
a(i*2,i)=1;
end
b
www.eeworm.com/read/366483/9812032
m radarsignal_hough.m
clear all
close all
clc
%对脉冲序列采样，每一个发射脉宽内采样10个单元(相当于取10个距离单元),采样时间间隔Ts=5e-7(相当于每个距离单元为Ts*c/2=75m).
c1=3e8; %speed of light
Te=5e-6; %发射脉冲宽度0.1ms
Be=1e6; %带宽 1M
www.eeworm.com/read/417715/10979305
m hough_lines.m
function [s,theta,acc]=hough_lines(varargin);
%HOUGH_LINES Hough transform line detection.
% CMP Vision Algorithms http://visionbook.felk.cvut.cz
%
% Find all straight lines in an image using the
www.eeworm.com/read/155037/6967768
m hough1.m
function [x,y,r,count]=hough1(BW1,x0,y0,r0,rr)
% BW1为输入的需检测的圆图象的矩阵,[x0,y0]为估算的定位中心的位置,r0为估算的定位的半径,
%rr是检测范围的外扩值
[m,n]=size(BW1);
%确定搜索范围，搜索的矩形的四个定点为[e3,e1],[e3,e2],[e4,e1],[e4,e2]
e1=floor(x0
www.eeworm.com/read/197486/7990969
m hough_l.m
img1=imread('K:\demo\photo\2123.jpg');
img= RGB2GRAY(img1)
edimg=edge(img);
s=size(img);
nr=s(1);
nth=s(2);
accarray=zeros(nr,nth);
rmax=sqrt(s(1)^2+s(2)^2);
dr=2*rmax/(nr-1);
dth=pi/nth;
www.eeworm.com/read/155035/6281190
m hough_circle.m
function [hough_space,hough_circle,para] = hough_circle(BW,step_r,step_angle,r_min,r_max,p)
%本算法采用最基本的三维空间处理算法，但是限制了一下半径的取值范围
% %%%%%%%%%%%%%%%%%%%%%%%%%%
% input
% BW:二值图像；
% step_r:检测的圆半径步长