Line & Circle & Blob Detection

Line detection

Line detection is performed by two methods

• Hough Lines: cv2.HoughLines(image, rho, theta, threshold) where:
  
  • image : binarized/thresholded image
  • rho : Distance resolution of the accumulator in pixels.
  • theta : Angle resolution of the accumulator in radians.
  • threshold : the minimum vote for it to be considered a line.
• Probabilistic Hough Lines : cv2.HoughLinesP(image, rho, theta, threshold, minLineLength, maxLineGap) where:
  
  • image : Ninarized/thresholded image
  • rho : Distance resolution of the accumulator in pixels.
  • theta : Angle resolution of the accumulator in radians.
  • threshold : The minimum vote for it to be considered a line.
  • minLineLength : The minimum pixels of line. default = 0.
  • maxLineGap : The gap of pixels between lines. default = 0.
    
    
    
    

Result

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Circle detection

Line detection is performed by:
cv2.HoughCircles(image, method, dp, minDist, param1, param2, minRadius, maxRadius) where:

• image : Binarized/thresholded image.
• method : Detection method.
• dp : Inverse ratio of accumulator resolution.
• minDist : The minimum distance between the center of detected circles.
• param1 : Gradient value used in the edge detection. default = 100.
• param2 : Accumulator threshold for the “method” (lower allows more circles to be detected (false positives)). default = 100.
• minRadius : Limits the smallest circle to this size (via radius). default = 0.
• maxRadius : Limits the biggest circle to this size (via radius). default = 0.
  
  
  
  

Method of HoughCircles

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• cv2.HOUGH_GRADIENT
• cv2.HOUGH_GRADIENT_ALT
  
  
  
  

Result

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Blob Detection

Blob detection is performed by:
cv2.drawKeypoints(image, keypoints, outImage, color, flags) where:

• image : The image detected by cv2.SimpleBlobDetector.create()
• keypoints : Keypoints from the source image.
• outImage : Output image. Its content depends on the flags value defining what is drawn in the output image.
• color : Color of keypoints. default = Scalar::all(-1)
• flags : Flags setting drawing features. Possible flags bit values are defined by DrawMatchesFlags. default = DRAW_MATCHES_FLAGS_DEFAULT
  
  
  
  

Flags of Blob detections

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• DRAW_MATCHES_FLAGS_DEFAULT
• DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS
• DRAW_MATCHES_FLAGS_DRAW_OVER_OUTIMG
• DRAW_MATCHES_FLAGS_NOT_DRAW_SINGLE_POINTS

Result

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Counting Blobs

We can count blobs by:
cv2.SimpleBlobDetector.Params()
We can set the filtering parameters of simpleBlobDetector. Let’s see what the parameters are in it.

We can set those parameters by:

params = cv2.SimpleBlobDetector.Params()

# Set Threshold filtering parameters
params.minThreshold = 10
params.maxThreshold = 200

# Set Area filtering parameters
params.filterByArea = True
params.minArea = 100

# Set Circularity filtering parameters
params.filterByCircularity = True 
params.minCircularity = 0.9

# Set Convexity filtering parameters
params.filterByConvexity = False
params.minConvexity = 0.2
    
# Set inertia filtering parameters
params.filterByInertia = True
params.minInertiaRatio = 0.01

# Create a detector with the parameters
detector = cv2.SimpleBlobDetector.create(params)
    
# Detect blobs
keypoints = detector.detect(image)

Result

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Implementation

• Line, Circle and Blob Detection
  
• Counting Circles, Ellipses and Finding Waldo