Binary Descriptors for Line Segments

This example shows the functionalities of lines extraction and descriptors computation furnished by cv.LSDDetector and cv.BinaryDescriptor classes.

In this tutorial it will be shown how to:

use the cv.BinaryDescriptor interface to extract lines and store them in KeyLine objects
use the same interface to compute descriptors for every extracted line

Sources:

Lines extraction and descriptors computation
Image
Initialize
Extract lines
Compute descriptors
Plot

Lines extraction and descriptors computation

In the following snippet of code, it is shown how to detect lines from an image. The LSD extractor is initialized with LSD_REFINE_ADV option; remaining parameters are left to their default values. A mask of ones is used in order to accept all extracted lines, which, at the end, are displayed using random colors for octave 0.

Once keylines have been detected, it is possible to compute their descriptors.

Image

% load image
if mexopencv.isOctave()
    im = fullfile(mexopencv.root(),'test','blox.jpg');
else
    im = which('cameraman.tif');
end
img = cv.imread(im, 'Color',true);

% create binary mask
mask = ones(size(img,1), size(img,2), 'uint8');

whos img mask

  Name        Size                Bytes  Class    Attributes

  img       256x256x3            196608  uint8              
  mask      256x256               65536  uint8

Initialize

% create BinaryDescriptor/LSDDetector objects with default parameters
bd = cv.BinaryDescriptor();
lsd = cv.LSDDetector();

Extract lines

keylinesBD = bd.detect(img, 'Mask',mask)
keylinesLSD = lsd.detect(img, 'Scale',2, 'NumOctaves',1, 'Mask',mask)

keylinesBD = 
  1×53 struct array with fields:
    angle
    class_id
    octave
    pt
    response
    size
    startPoint
    endPoint
    startPointInOctave
    endPointInOctave
    lineLength
    numOfPixels
keylinesLSD = 
  1×166 struct array with fields:
    angle
    class_id
    octave
    pt
    response
    size
    startPoint
    endPoint
    startPointInOctave
    endPointInOctave
    lineLength
    numOfPixels

Compute descriptors

descriptorsBD = bd.compute(img, keylinesBD);
descriptorsLSD = bd.compute(img, keylinesLSD);
whos descriptorsBD descriptorsLSD

  Name                  Size            Bytes  Class    Attributes

  descriptorsBD        53x32             1696  uint8              
  descriptorsLSD      166x32             5312  uint8

Plot

% lines extracted from octave 0
keylinesBD = keylinesBD([keylinesBD.octave] == 0);
keylinesLSD = keylinesLSD([keylinesLSD.octave] == 0);

% draw line between extremes using random colors
outBD = img;
outLSD = img;
for i=1:numel(keylinesBD)
    outBD = cv.line(outBD, keylinesBD(i).startPoint, keylinesBD(i).endPoint, ...
        'Color',randi([0 255],[1 3]), 'Thickness',3);
end
for i=1:numel(keylinesLSD)
    outLSD = cv.line(outLSD, keylinesLSD(i).startPoint, keylinesLSD(i).endPoint, ...
        'Color',randi([0 255],[1 3]), 'Thickness',3);
end
subplot(121), imshow(outBD), title('BD Lines')
subplot(122), imshow(outLSD), title('LSD Lines')