Tutorial 56 - Blob Detector for segmentation based on feature properties (in python)
BLOB stands for Binary Large OBject and refers to a group of connected pixels in a binary image. A Blob is a group of connected pixels in an image that share some common property ( e.g. grayscale value ). The goal of blob detection is to identify and mark these connected regions.
How it works:
1. Threshold input images to binary.
2. Grouping: connected white/black pixels are grouped together.
3. Merging: blobs located closer than minDistBetweenBlobs are merged.
4. Center & Radius Calculation : The centers and radii of the new merged blobs are computed and returned.
Can be filtered by color, size or shape
References:
https://www.learnopencv.com/blob-dete...
Code associated with these tutorials can be downloaded from here: https://github.com/bnsreenu/python_fo...
Watch video Tutorial 56 - Blob Detector for segmentation based on feature properties (in python) online without registration, duration hours minute second in high quality. This video was added by user ZEISS arivis 27 July 2020, don't forget to share it with your friends and acquaintances, it has been viewed on our site 12,613 once and liked it 187 people.