from：http://blog.sina.com.cn/s/blog_736aa0540101kzqb.html
clc; clear; close all;
% Haar-like特征矩形计算
board = 24 % 检测窗口宽度
num = 24 % 检测窗口分划数
show = 1; % 1为作图
time = 0.001; % 作图间隔
%%
if mod(board,num)~=0
error(\'检测窗口宽度必须是分划数的整数倍\')
else
delta = board/num % 滑动步进值
end
%% Haar特征1：左白,右黑,(s,t)=(1,2)
s = 1;
t = 2;
R = s:s:floor(num/s)*s; % Haar窗口高
C = t:t:floor(num/t)*t; % Haar窗口宽
NUM = 0; % Haar特征总数
\'---- Haar特征1：左白,右黑,(s,t)=(1,2) ---\'
for I = 1:length(R)
for J = 1:length(C)
r = R(I)*delta; % Haar窗口高
c = C(J)*delta; % Haar窗口宽
nr = num-R(I)+1; % 行方向移动个数
nc = num-C(J)+1; % 列方向移动个数
Px0 = [0 r]; % 矩形坐标初始化
Py0 = [0 c/2 c];
for i = 1:nr
for j = 1:nc
Px = Px0+(i-1)*delta; % 滑动取点
Py = Py0+(j-1)*delta;
NUM = NUM+1;
if show
plot([0 board],repmat((0:delta:board)\',1,2),\'k\'); hold on;
plot(repmat((0:delta:board)\',1,2),[0 board],\'k\'); axis tight; axis square;
title(\'Haar矩形遍历演示\');xlabel(\'x\');ylabel(\'y\');
plot(Px,repmat(Py\',1,2),\'r\',\'LineWidth\',5)
plot(repmat(Px,2,1),repmat([Py(1) Py(end)]\',1,2),\'r\',\'LineWidth\',5); hold off
pause(time)
end
end
end
end
end
NUM
%% Haar特征2：上白,下黑,(s,t)=(2,1)
s = 2;
t = 1;
R = s:s:floor(num/s)*s; % Haar窗口高
C = t:t:floor(num/t)*t; % Haar窗口宽
NUM = 0; % Haar特征总数
\'---- Haar特征2：上白,下黑,(s,t)=(2,1) ---\'
for I = 1:length(R)
for J = 1:length(C)
r = R(I)*delta; % Haar窗口高
c = C(J)*delta; % Haar窗口宽
nr = num-R(I)+1; % 行方向移动个数
nc = num-C(J)+1; % 列方向移动个数
Px0 = [0 r/2 r]; % 矩形坐标初始化
Py0 = [0 c];
for i = 1:nr
for j = 1:nc
Px = Px0+(i-1)*delta; % 滑动取点
Py = Py0+(j-1)*delta;
NUM = NUM+1;
if show
plot([0 board],repmat((0:delta:board)\',1,2),\'k\'); hold on;
plot(repmat((0:delta:board)\',1,2),[0 board],\'k\'); axis tight; axis square;
title(\'Haar矩形遍历演示\');xlabel(\'x\');ylabel(\'y\');
plot(repmat(Px,2,1),repmat(Py\',1,length(Px)),\'r\',\'LineWidth\',3);
plot(repmat([Px(1) Px(end)]\',1,2),repmat(Py,2,1),\'r\',\'LineWidth\',3); hold off
pause(time)
end
end
end
end
end
NUM
%% Haar特征3：左右白,中间黑,(s,t)=(1,3)
s = 1;
t = 3;
R = s:s:floor(num/s)*s; % Haar窗口高
C = t:t:floor(num/t)*t; % Haar窗口宽
NUM = 0; % Haar特征总数
\'---- Haar特征3：左右白,中间黑,(s,t)=(1,3) ---\'
for I = 1:length(R)
for J = 1:length(C)
r = R(I)*delta; % Haar窗口高
c = C(J)*delta; % Haar窗口宽
nr = num-R(I)+1; % 行方向移动个数
nc = num-C(J)+1; % 列方向移动个数
Px0 = [0 r]; % 矩形坐标初始化
Py0 = [0 c/3 c*2/3 c];
for i = 1:nr
for j = 1:nc
Px = Px0+(i-1)*delta; % 滑动取点
Py = Py0+(j-1)*delta;
NUM = NUM+1;
if show
plot([0 board],repmat((0:delta:board)\',1,2),\'k\'); hold on;
plot(repmat((0:delta:board)\',1,2),[0 board],\'k\'); axis tight; axis square;
title(\'Haar矩形遍历演示\');xlabel(\'x\');ylabel(\'y\');
plot(Px,repmat(Py\',1,2),\'r\',\'LineWidth\',5)
plot(repmat(Px,2,1),repmat([Py(1) Py(end)]\',1,2),\'r\',\'LineWidth\',5); hold off
pause(time)
end
end
end
end
end
NUM
%% Haar特征4：左右白,中间黑(2倍宽度),(s,t)=(1,4)
s = 1;
t = 4;
R = s:s:floor(num/s)*s; % Haar窗口高
C = t:t:floor(num/t)*t; % Haar窗口宽
NUM = 0; % Haar特征总数
\'---- Haar特征4：左右白,中间黑(2倍宽度),(s,t)=(1,4) ---\'
for I = 1:length(R)
for J = 1:length(C)
r = R(I)*delta; % Haar窗口高
c = C(J)*delta; % Haar窗口宽
nr = num-R(I)+1; % 行方向移动个数
nc = num-C(J)+1; % 列方向移动个数
Px0 = [0 r]; % 矩形坐标初始化
Py0 = [0 c/4 c*3/4 c];
for i = 1:nr
for j = 1:nc
Px = Px0+(i-1)*delta; % 滑动取点
Py = Py0+(j-1)*delta;
NUM = NUM+1;
if show
plot([0 board],repmat((0:delta:board)\',1,2),\'k\'); hold on;
plot(repmat((0:delta:board)\',1,2),[0 board],\'k\'); axis tight; axis square;
title(\'Haar矩形遍历演示\');xlabel(\'x\');ylabel(\'y\');
plot(Px,repmat(Py\',1,2),\'r\',\'LineWidth\',5)
plot(repmat(Px,2,1),repmat([Py(1) Py(end)]\',1,2),\'r\',\'LineWidth\',5); hold off
pause(time)
end
end
end
end
end
NUM
%% Haar特征5：上下白，中间黑,(s,t)=(3,1)
s = 3;
t = 1;
R = s:s:floor(num/s)*s; % Haar窗口高
C = t:t:floor(num/t)*t; % Haar窗口宽
NUM = 0; % Haar特征总数
\'---- Haar特征5：上下白，中间黑,(s,t)=(3,1) ---\'
for I = 1:length(R)
for J = 1:length(C)
r = R(I)*delta; % Haar窗口高
c = C(J)*delta; % Haar窗口宽
nr = num-R(I)+1; % 行方向移动个数
nc = num-C(J)+1; % 列方向移动个数
Px0 = [0 r/3 r*2/3 r]; % 矩形坐标初始化
Py0 = [0 c];
for i = 1:nr
for j = 1:nc
Px = Px0+(i-1)*delta; % 滑动取点
Py = Py0+(j-1)*delta;
NUM = NUM+1;
if show
plot([0 board],repmat((0:delta:board)\',1,2),\'k\'); hold on;
plot(repmat((0:delta:board)\',1,2),[0 board],\'k\'); axis tight; axis square;
title(\'Haar矩形遍历演示\');xlabel(\'x\');ylabel(\'y\');
plot(repmat(Px,2,1),repmat(Py\',1,length(Px)),\'r\',\'LineWidth\',3);
plot(repmat([Px(1) Px(end)]\',1,2),repmat(Py,2,1),\'r\',\'LineWidth\',3); hold off
pause(time)
end
end
end
end
end
NUM
%% Haar特征6：上下白，中间黑(2倍宽度),(s,t)=(4,1)
s = 4;
t = 1;
R = s:s:floor(num/s)*s; % Haar窗口高
C = t:t:floor(num/t)*t; % Haar窗口宽
NUM = 0; % Haar特征总数
\'---- Haar特征6：上下白，中间黑(2倍宽度),(s,t)=(4,1) ---\'
for I = 1:length(R)
for J = 1:length(C)
r = R(I)*delta; % Haar窗口高
c = C(J)*delta; % Haar窗口宽
nr = num-R(I)+1; % 行方向移动个数
nc = num-C(J)+1; % 列方向移动个数
Px0 = [0 r/4 r*3/4 r]; % 矩形坐标初始化
Py0 = [0 c];
for i = 1:nr
for j = 1:nc
Px = Px0+(i-1)*delta; % 滑动取点
Py = Py0+(j-1)*delta;
NUM = NUM+1;
if show
plot([0 board],repmat((0:delta:board)\',1,2),\'k\'); hold on;
plot(repmat((0:delta:board)\',1,2),[0 board],\'k\'); axis tight; axis square;
title(\'Haar矩形遍历演示\');xlabel(\'x\');ylabel(\'y\');
plot(repmat(Px,2,1),repmat(Py\',1,length(Px)),\'r\',\'LineWidth\',3);
plot(repmat([Px(1) Px(end)]\',1,2),repmat(Py,2,1),\'r\',\'LineWidth\',3); hold off
pause(time)
end
end
end
end
end
NUM
%% Haar特征7：左上右下白，其它黑,(s,s)=(2,2)
s = 2;
t = 2;
R = s:s:floor(num/s)*s; % Haar窗口高
C = t:t:floor(num/t)*t; % Haar窗口宽
NUM = 0; % Haar特征总数
\'---- Haar特征7：左上右下白，其它黑,(s,s)=(2,2) ---\'
for I = 1:length(R)
for J = 1:length(C)
r = R(I)*delta; % Haar窗口高
c = C(J)*delta; % Haar窗口高
nr = num-R(I)+1; % 行方向移动个数
nc = num-C(J)+1; % 行方向移动个数
Px0 = [0 r/2 r]; % 矩形坐标初始化
Py0 = [0 c/2 c]; % 矩形坐标初始化
for i = 1:nr
for j = 1:nc
Px = Px0+(i-1)*delta; % 滑动取点
Py = Py0+(j-1)*delta;
NUM = NUM+1;
if show
plot([0 board],repmat((0:delta:board)\',1,2),\'k\'); hold on;
plot(repmat((0:delta:board)\',1,2),[0 board],\'k\'); axis tight; axis square;
title(\'Haar矩形遍历演示\');xlabel(\'x\');ylabel(\'y\');
plot(repmat(Px,3,1),repmat(Py\',1,length(Px)),\'r\',\'LineWidth\',3);
plot(repmat([Px(1) Px(end)]\',1,3),repmat(Py,2,1),\'r\',\'LineWidth\',3); hold off
pause(time)
end
end
end
end
end
NUM
%% Haar特征8：四周白，中间黑,(s,s)=(3,3)
s = 3;
t = 3;
R = s:s:floor(num/s)*s; % Haar窗口高
C = t:t:floor(num/t)*t; % Haar窗口宽
NUM = 0; % Haar特征总数
\'---- Haar特征8：四周白，中间黑,(s,s)=(3,3) ---\'
for I = 1:length(R)
for J = 1:length(C)
r = R(I)*delta; % Haar窗口高
c = C(J)*delta; % Haar窗口高
nr = num-R(I)+1; % 行方向移动个数
nc = num-C(J)+1; % 行方向移动个数
Px0 = [0 r/3 r*2/3 r]; % 矩形坐标初始化
Py0 = [0 c/3 c*2/3 c]; % 矩形坐标初始化
for i = 1:nr
for j = 1:nc
Px = Px0+(i-1)*delta; % 滑动取点
Py = Py0+(j-1)*delta;
NUM = NUM+1;
if show
plot([0 board],repmat((0:delta:board)\',1,2),\'k\'); hold on;
plot(repmat((0:delta:board)\',1,2),[0 board],\'k\'); axis tight; axis square;
title(\'Haar矩形遍历演示\');xlabel(\'x\');ylabel(\'y\');
plot(repmat(Px,4,1),repmat(Py\',1,length(Px)),\'r\',\'LineWidth\',3);
plot(repmat([Px(1) Px(end)]\',1,4),repmat(Py,2,1),\'r\',\'LineWidth\',3); hold off
pause(time)
end
end
end
end
end
NUM
% 毕业院校：海军工程大学，水声工程专业，博士
% 精通方向：数字信号(图像、视频)处理，人工智能与模式识别，群体智能优化，非线性与混沌，支持向量机，Matlab与VC++混编
% 现任岗位：沈阳聚德视频技术有限公司，图像处理及模式识别研发工程师
% 工作职责：车牌识别，视频目标跟踪等算法开发，C/C++实现，DSP植入
% 兴趣爱好：金融时序的程式化交易
%
% 主要成果：
% [1] 实现车牌识别C/C实现，DSP植入，识别率：汉字不低于99%，数字字母不低于99.5%，整牌不低于97%
% [2] 精通数字信号(图像、视频)“特征提取”与“模式识别”的研究与开发，开展了“支持向量机”应用研究，原创文章有《四种支持向量机工具箱使用要点》，独立开发了“支持向量机Matlab工具箱Version1.0”。结题项目有：语音信号处理与识别，遥感图像的特征提取与分类，人脸识别，主被动声纳信号处理与识别等
% [3] 精通“群体智能优化”，原创工具箱有“群体智能算法”Matlab工具箱 Version2.0”，误差精度优于现有公开发表文献，工程中解决了各种高维复杂问题的优化计算
% [4] 精通“时间序列混沌建模和预测”，基于Matlab和VC 混编平台，独立开发了混沌分析和预测软件包“混沌时间序列分析与预测工具箱 Version2.9”。结题项目有：金融数据波动性分析与程式化交易，银行反洗钱异常检测系统，混沌背景弱信号检测，海洋混响背景弱目标检测等
% [5] 精通Matlab与VC 混合编程：(a)以VC 为界面，核心算法采用Matlab函数，原创文章有《如何将Matlab7.0函数转换成VC 6.0动态链接库》；(b)以Matlab为界面，耗时算法在VC 环境中采用Mexfunction编译。
%
% 联系方式
电子邮件：[email protected]
