Tutorial 56 - Blob Detector for segmentation based on feature properties (in python)

Опубликовано: 27 Июль 2020
на канале: ZEISS arivis
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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...


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