使用Hough变换自动删除直线

时间:2018-06-07 08:17:21

标签: matlab image-processing ocr image-segmentation hough-transform

我正在做一篇关于光学字符识别的论文。我的工作是从图像中正确分割文本字符。

问题是,该语言中的每个文本行都有单词,其中字符通常用直线连接。这些线的厚度可以相同,也可以不同。

到目前为止,使用投影配置文件,我已经能够分割未连接到任何直线的字符。但要分割由直线连接的字符,我必须删除这些行。我更喜欢使用Hough变换来检测和删除那些线(意味着在BW图像中,如果线中的像素是黑色,则将其变为白色)。

查看包含文字的示例图片: Sample Image

This是使用投影配置文件从上图分割的线。

These是使用Hough变换检测到的行。

霍夫变换代码。使用This图片对其进行测试。

I = imread('line0.jpg');
%I = rgb2gray(I);
BW = edge(I,'canny');
[H,T,R] = hough(BW);
imshow(H,[],'XData',T,'YData',R,'InitialMagnification','fit');
xlabel('\theta'),ylabel('\rho');
axis on, axis normal, hold on;
P = houghpeaks(H,1,'threshold',ceil(0.3*max(H(:))));
x = T(P(:,2));
y = R(P(:,1));
plot(x,y,'s','color','blue');

% Find lines and plot them
lines = houghlines(BW,T,R,P,'FillGap',5,'MinLength',7);
figure, imshow(I), hold on
grid on
max_len = 0;

for k = 1:length(lines)
    xy = [lines(k).point1;lines(k).point2];
    plot(xy(:,1),xy(:,2),'LineWidth',1,'Color','green');

    % plot beginnings and ends of lines
    plot(xy(1,1),xy(1,2),'o','LineWidth',2,'Color','red');
    plot(xy(2,1),xy(2,2),'o','LineWidth',2,'Color','blue');

    % determine the endpoints of the longest line segment
    len = norm(lines(k).point1 - lines(k).point2);
    if( len > max_len )
        max_len = len;
        xy_long = xy;
    end
end

关于我如何做到的任何想法?任何帮助将不胜感激!

1 个答案:

答案 0 :(得分:1)

houghlines开始,您只需要用白色替换该行的索引(在本例中为255)。您可能需要稍微使用填充,以取消一个或两个以上的像素。

编辑:这是一个版本尝试确定填充。

%% OCR
I = imread('CEBML.jpg');
BW = edge(I,'canny');
[H,T,R] = hough(BW);
P = houghpeaks(H,1,'threshold',ceil(0.3*max(H(:))));
x = T(P(:,2));
y = R(P(:,1));

% Find lines and plot them
lines = houghlines(BW,T,R,P,'FillGap',5,'MinLength',7);
subplot(2,1,1)
grid on
imshow(I)
title('Input')
hold on
px = 5; % Number of padding pixels to probe
white_threshold = 30; % White threshold
ln_length = .6; % 60 %
for k = 1:length(lines)
    xy = [lines(k).point1; lines(k).point2];
    buf_y = xy(1,1):xy(2,1); % Assuming it's a straight line!
    buf_x = [repmat(xy(1,2),1,xy(2,1) - xy(1,1)),xy(2,2)] +  [-px:px]';
    I_idx = sub2ind(size(I),buf_x, repmat(buf_y,size(buf_x,1),1));
    % Consider lines that are below white threshold, and are longer than xx
    % of the found line.
    idx = sum(I(I_idx) <= white_threshold,2) >= ln_length * size(I_idx,2);
    I(I_idx(idx,:)) = 255;

    % Some visualisation 
    [ixx,jyy] = ind2sub(size(I),I_idx(idx,:));
    plot(jyy,ixx,'.r');% Pixels set to white 
    plot(xy(:,1),xy(:,2),'-b','LineWidth',2);  % Found lines
end
subplot(2,1,2)
grid on
imshow(I)
title('Output')

enter image description here