如何从投影图中准确获取线段？

Question

所以这基本上是一件非常简单的事情，就像只获取水平投影图并从中获取图像上线条的位置。但问题是所应用的阈值是非常可变的。如果我保持在安全级别，则会提取正确数量的行，而另一方面会提取不需要的结果。

例如这里是图片：

及其水平投影：

这是我用来提取文本行的代码：

%complementing as text must be non zero and background should be 0
img_comp = imcomplement(img);

%calculate the horizontal projections and plot it to verify the threshold
horizontal_projections = sum(img_comp, 2);
plot(horizontal_projections)

%A very crude method of automatically detecting the threshold

proj_mean = mean(horizontal_projections);
lines = horizontal_projections > floor(proj_mean); 

% Find Rising and falling edges
d = diff(lines);
startingColumns = find(d>0);
endingColumns = find(d<0);

% Extract each line and save it in a cell
for lines_k = 1 : length(startingColumns)
  lines_extracted{lines_k} = img(startingColumns(lines_k):endingColumns(lines_k), :);
end

我想自动选择阈值，但遇到了麻烦，如果我使用代码中显示的阈值作为预测的平均值，它会提取 9 行正确但这些行会丢失大量数据，如：

这是第二行，字母的延长线和降线都被剪掉了。使用平均值的一半或三分之一是可行的，但它对每张图像都不同，而且根本不会自动化。

Answer 1

如何转换为 YCbCr 色彩空间？使用维基百科的转换公式。

img = im2double(imread('StackOverflow-Example.jpg'));
rp = img(:, :, 1) / 255 ;
bp = img(:, :, 2) / 255 ;
gp = img(:, :, 3) / 255 ;
kb = 0.114;
kr = 0.299;
y = kr * rp + (1 - kr - kb) * gp + kb * bp;
y = max(max(y))-y;
y = y ./ y;
surf(y,'EdgeColor','none','LineStyle','none')
view(0, -90)

维护信息看起来不错。

编辑：

我想你想要每一行

%% Load image and find intensity %%
img = im2double(imread('test.jpg')); % load image and convert to doubles to allow for calculations
rp = img(:, :, 1) / 255 ; % normalized red portion
bp = img(:, :, 2) / 255 ; % normalized blue portion
gp = img(:, :, 3) / 255 ; % normalized green portion
kb = 0.114; % blue constant from Wikipedia
kr = 0.299; % red constant from Wikipedia
x = kr * rp + (1 - kr - kb) * gp + kb * bp; % normalized intensity in image
x = max(max(x))-x; % removed background

y = x ./ x; % everything left is high

z = y;
z(isnan(y)) = 0; % turn nan's to zero
divisions = find(sum(z,2) > 5); % find all lines that have less than 5 pixels
divisions = [divisions(1); divisions(diff(divisions) > 10); size(z, 1)]; % find the line breaks

rows = cell(length(divisions), 1);

for i = 1:numel(rows)-1
    line = z(divisions(i):divisions(i+1), :); % grab line
    j = divisions(i) + find(sum(line,2) > 5) - 1; % remove the white space
    line = y(j, :);
    rows{i} = line; %store the line
end

rows(numel(rows)) = [];

%% plot each line %%
for i = 1:numel(rows) ; 
    figure(i) ; 
    surf(rows{i},'EdgeColor','none','LineStyle','none');
    view(0, -90) ;
end

%% plot entire page %%
figure(numel(rows) + 1)
surf(y,'EdgeColor','none','LineStyle','none') % plot of entire image
view(0, -90)

编辑：格林威治标准时间 2015/05/18 15:45

这具有剩余的强度值：

img = im2double(imread('test.jpg'));
rp = img(:, :, 1) / 255 ;
bp = img(:, :, 2) / 255 ;
gp = img(:, :, 3) / 255 ;
kb = 0.114;
kr = 0.299;
x = kr * rp + (1 - kr - kb) * gp + kb * bp;
x = max(max(x))-x;
xp = x;
xp(xp == min(min(xp))) = nan;

y = x ./ x;

z = y;
z(isnan(y)) = 0;
divisions = find(sum(z,2) > 5);
divisions = [divisions(1); divisions(diff(divisions) > 10); size(z, 1)];

rows = cell(length(divisions) - 1, 1);

for i = 1:numel(rows)
    line = z(divisions(i):divisions(i+1), :);
    j = divisions(i) + find(sum(line,2) > 5) - 1;
    line = xp(j, :);
    rows{i} = line;

    figure(i) ; 
    surf(rows{i},'EdgeColor','none','LineStyle','none');
    axis('equal')
    view(0, -90) ;
end

figure(numel(rows) + 1)
surf(xp,'EdgeColor','none','LineStyle','none')
axis('equal')
view(0, -90)

---

编辑 2015-05-22 13:21 GMT

%Turn warning message off
warning('off', 'Images:initSize:adjustingMag');

%Read in image in int8
originalImg = imread('test.jpg');

%Convert to double
img = im2double(originalImg);

%Take R, G, & B components
rp = img(:, :, 1) ;
gp = img(:, :, 2) ;
bp = img(:, :, 3) ;

%Get intensity
kb = 0.114;
kr = 0.299;
yp = kr * rp + (1 - kr - kb) * gp + kb * bp;

%Flip to opposite of intensity
ypp = max(max(yp))-yp;

%Normalize flipped intensity
z = ypp ./ ypp;
z(isnan(z)) = 0;

%Find lines, this may need to be tuned
MaxPixelsPerLine = 5;
MinRowsPerLine = 10;
divisions = find(sum(z,2) > MaxPixelsPerLine);
divisions = [divisions(1); divisions(diff(divisions) > MinRowsPerLine); size(z, 1)];

%Preallocate for number of lines
colorRows = cell(length(divisions) - 1, 1);

for i = 1:numel(rows)
    %Extract the lines in RGB
    line = z(divisions(i):divisions(i+1), :);
    j = divisions(i) + find(sum(line,2) > 5) - 1;
    colorRows{i} = originalImg(j, :, :);

    %Print out the line
    figure(i) ;
    imshow(colorRows{i})
end

%Print out the oringinal image
figure(numel(rows) + 1)
imshow(originalImg)

%Turn the warning back on
warning('on', 'Images:initSize:adjustingMag');

Answer 2

简短： graythresh(img) 可以解决您的问题

更长：

使用一些形态学方法，您可以很容易地提取线条。不过有个小缺点：它们有点乱。

加载你的图片

original = imread('o6WEN.jpg'); 

把它变成灰度

img=rgb2gray(original); .

用大约 textheight 和 'very' long 定义一个矩形结构元素

se = strel('rectangle',[30 200]); 

用顶帽过滤器过滤它。在此之后，具有大约 textheight 的长矩形将更加突出。

 img = imtophat(img,se);

调整对比度：

img = imadjust(img);

定义另一个结构元素，这次比 textheight 短一点：

se = strel('line',20,0);

用它放大图片以消除字母之间存在的空白

img = imdilate(img,se);

将图像变为黑色并带有：

img=im2bw(img,graythresh(img));

使用 regionprops 让所有 BoundingBoxes 形成你的线条

 stats=regionprops(img,'BoundingBox');
 figure, imshow(img)

In Stats 现在是你所有行的边界框，遗憾的是乱序。也许这可以通过 BWlables 或某种相关性来纠正。 我只是查看了 BoundingBoxes 的 y 坐标并进行了相应的排序。

BoundingBoxes=struct2cell(stats);
BoundingBoxes=cell2mat(BoundingBoxes'); % making it into an array
[~,ind]=sort(BoundingBoxes(:,2)); % sorting it to y
BoundingBoxes=BoundingBoxes(ind,:); % apply the sorted vector 

 lineNr=8;
imshow(original(BoundingBoxes(2,lineNr):BoundingBoxes(2,lineNr)+BoundingBoxes(4,lineNr),BoundingBoxes(1,lineNr):BoundingBoxes(1,lineNr)+BoundingBoxes(3,lineNr)  ))

希望对你有用