Blob-Detect

Blob 是什麼

一個Blob是在一張圖片中共享一些諸如灰度值等屬性的一組鏈接的像素點。在上圖中，黑色的鏈接區域就是blob，blob detection的目標就是識別並標記這些區域。

 

Blob detection 工做原理

SimpleBlobDetector, 是很是簡單的模塊，算法使用以下參數控制，且執行以後的流程：

• Thresholding: 將源圖轉爲一些二值圖，使用從minThreshold開始的閾值. 閾值從minThreshold開始，使用thresholdStep爲梯度增長.
• Grouping: 在每一個二值圖中，相鄰的白色像素點是被group在一塊兒的，稱之爲binary blobs。
• Merging: 計算二值圖片中binary blobs的中心點，blobs之間的距離比minDistBetweenBlobs更小的會被合併。
• Center & Radius Calculation: 計算並返回新合併的blobs的中心和半徑。

 

利用color, size, shape 過濾 Blobs

• By Color : [ Note : This feature appears to be broken. I checked the code, and it appears to have a logical error ] First you need to set filterByColor = 1. Set blobColor = 0 to select darker blobs, and blobColor = 255 for lighter blobs.

• By Size : You can filter the blobs based on size by setting the parameters filterByArea = 1, and appropriate values for minArea and maxArea. E.g. setting minArea = 100 will filter out all the blobs that have less then 100 pixels.

• By Shape : Now shape has three different parameters.

 

Circularity

This just measures how close to a circle the blob is. E.g. a regular hexagon has higher circularity than say a square. To filter by circularity, set filterByCircularity = 1. Then set appropriate values for minCircularity and maxCircularity. Circularity is defined as

This means that a circle has a circularity of 1, circularity of a square is 0.785, and so on.

 

Convexity

A picture is worth a thousand words. Convexity is defined as the (Area of the Blob / Area of it’s convex hull). Now, Convex Hull of a shape is the tightest convex shape that completely encloses the shape. To filter by convexity, set filterByConvexity = 1, followed by setting 0 ≤ minConvexity ≤ 1 and maxConvexity ( ≤ 1)

Inertia Ratio¶

Don’t let this scare you. Mathematicians often use confusing words to describe something very simple. All you have to know is that this measures how elongated a shape is. E.g. for a circle, this value is 1, for an ellipse it is between 0 and 1, and for a line it is 0. To filter by inertia ratio, set filterByInertia = 1, and set 0 ≤ minInertiaRatio ≤ 1 and maxInertiaRatio (≤ 1 ) appropriately.

 

 

下例將展現各個參數對標準圖塊的選取影響：

 

import env
from mvlib import *
from mvlib.application import *

 

# Read image
im = read_image("blob.jpg")
im_gray = gray(im)
dev_imshow(im_gray)

blob_detect_params = create_blob_detector_params(10, 200, minArea=1500, minCircularity=0.1, minConvexity=0.87, minInertiaRatio=0.01)
detector = create_blob_detector(blob_detect_params)

# Detect blobs.
keypoints = detector.detect(im_gray)

# Draw detected blobs as red circles.
# cv2.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS ensures
# the size of the circle corresponds to the size of blob
im_with_keypoints = dev_draw_keypoints(im, keypoints)
dev_imshow(im_with_keypoints)

 

https://www.learnopencv.com/blob-detection-using-opencv-python-c/

https://blog.csdn.net/jinntaoo/article/details/82255829