BLOB是图像中灰度块的一种专业称呼，更加变通一点的可以说它跟我们前面二值图像分析的联通组件类似，通过特征提取中的SimpleBlobDetector可以实现常见的各种灰度BLOB对象组件检测与分离。使用该检测器的时候，可以根据需要输入不同参数，得到的结果跟输入的参数息息相关。常见的BLOB分析支持如下：
- 根据BLOB面积过滤
- 根据灰度/颜色值过滤
- 根据圆度过滤
- 根据长轴与短轴过滤
- 根据凹凸进行过滤
参数列表:
SimpleBlobDetector::Params::Params()
bool filterByArea
bool filterByCircularity
bool filterByColor
bool filterByConvexity
bool filterByInertia
float maxArea
float maxCircularity
float maxConvexity
float maxInertiaRatio
float maxThreshold
float minArea
float minCircularity
float minConvexity
float minDistBetweenBlobs
float minInertiaRatio
代码：
import cv2 as cv
import numpy as np
# load image
frame = cv.imread("zhifang_ball.png")
gray = cv.cvtColor(frame, cv.COLOR_BGR2GRAY)
params = cv.SimpleBlobDetector_Params()
# Change thresholds
params.minThreshold = 0;
params.maxThreshold = 256;
# Filter by Area.
params.filterByArea = True
params.minArea = 100
# Filter by Circularity
params.filterByCircularity = True
params.minCircularity = 0.1
# Filter by Convexity
params.filterByConvexity = True
params.minConvexity = 0.5
# Filter by Inertia
params.filterByInertia = True
params.minInertiaRatio = 0.5
detector = cv.SimpleBlobDetector_create(params)
# Detect blobs.
cv.imshow("input", frame)
keypoints = detector.detect(gray)
result = cv.drawKeypoints(frame, keypoints, None, (0, 0, 255), cv.DRAW_MATCHES_FLAGS_DRAW_RICH_KEYPOINTS)
cv.imshow("result", result)
cv.imwrite("result.png", result)
cv.waitKey(0)
cv.destroyAllWindows()