Finds line segments in a binary image using the probabilistic Hough transform

lines = cv.HoughLinesP(image)
lines = cv.HoughLinesP(..., 'OptionName', optionValue, ...)

Input

• image 8-bit, single-channel binary source image.

Output

• lines Output vector of lines. A cell-array of 4-element vectors {[x1,y1,x2,y2], ...}, where (x1,y1) and (x2,y2) are the ending points of each detected line segment.

Options

• Rho Distance resolution of the accumulator in pixels. default 1.
• Theta Angle resolution of the accumulator in radians. default pi/180.
• Threshold Accumulator threshold parameter. Only those lines are returned that get enough votes (>Threshold). default 80.
• MinLineLength Minimum line length. Line segments shorter than that are rejected. default 0.
• MaxLineGap Maximum allowed gap between points on the same line to link them. default 0.

The function implements the probabilistic Hough transform algorithm for line detection, described in [Matas00].

References

[Matas00]:

Jiri Matas, Charles Galambos, and Josef Kittler. Robust detection of lines using the progressive probabilistic hough transform. Computer Vision and Image Understanding, 78(1):119-137, 2000.