Improving line extraction from HoughLinesP

asked 2015-03-04 08:55:57 -0600

bvbdort
115 ●3 ●7

updated 2015-03-04 09:14:45 -0600

Hi,

I am using HoughLinesP to extract lines from grayscale image.

Below is my psudo code.

threshold(img_tmp,bin_img,30,255,cv::THRESH_BINARY);
Canny(bin_img, canny_img, 50, 255, 3);
vector<Vec4i> tmp_lines;
HoughLinesP(canny_img,tmp_lines, 1, CV_PI/360,10, 10, 1);

As seen in below image single edge (i.e single line in image) is returning more than one line. 16,22 and 0,28 and 10,11 and 23,18,24 lines correspond to single line.

How can i get single line for single edge, any suggestions ?

Input image:

Input image

Extracted lines

image description

Zoomed image

image description

thanks.

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Comments

You should increase the last parameter: "maxLineGap – Maximum allowed gap between points on the same line to link them."

kbarni ( 2015-03-04 09:38:14 -0600 )edit

i tried it and didnt solve, here the issue i guess due to width of the edge

bvbdort ( 2015-03-04 11:52:08 -0600 )edit

I see that you are using a large angular accumulator (CV_PI/360=0.5°). That means that if there is a minimal difference between the line directions, they will be considered as separate lines. try to use different values for this parameter ( as your lines are a bit "noisy", you can go up to CV_PI/36 = 5°). It will eventually detect more lines, too.

kbarni ( 2015-03-05 02:50:59 -0600 )edit

i tried with 1° and 5° but the result was same.

bvbdort ( 2015-03-05 04:13:18 -0600 )edit

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answered 2015-03-05 08:29:43 -0600

kbarni

4134 ●1 ●13 ●49

updated 2015-03-05 08:32:13 -0600

I checked your code; the first problem is that you already have an edge image. If you run a Canny filter, it will encircle your walls, giving you a lot of false edges. That's why you got generally two lines on both sides of your original line (you can see it on the magnified image).

So use just the thresholded image (just convert it to grayscale):

threshold(img_tmp,bin_img,30,255,cv::THRESH_BINARY_INV);
cvtColor(bin_img, bin_img, COLOR_BGR2GRAY);

Then, you should play with the parameters of the Hough transform. As the image is noisy (the lines aren't straight), increment the rho and theta resolutions. I got quite good results with the following parameters:

HoughLinesP(bin_img,tmp_lines, 2, CV_PI/36, 10, 10, 1);

Here is my result (37 lines detected):

Result

For better results, you must use more sophisticated algorithms (e.g. marked point processes with a linear model - but you won't find these in OpenCV).

Comments

thanks for the answer. Yes this result was better. But using 5° is not good for my case. Since i was using line angle for further calculation. Also i can see that the line 38 from a edge because of line. I am using it with 1° and you answer is helpful.

bvbdort ( 2015-03-05 15:14:44 -0600 )edit

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Improving line extraction from HoughLinesP

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