Three techniques for Image Segmentation

An implementation with Python

Image segmentation is a technique used in Computer Vision whose goal is that of partitioning a given image into segments, in order to output a data representation that is more meaningful than the original image.

There are two ways we can perform image segmentations:

• Semantic segmentation →it considers as the same instance all the items which belong to the same semantic category. Namely, it will let fall within the same segment all the instances which represent dogs.

source: https://www.warrenphotographic.co.uk/11238-two-pomeranians-with-paws-over

• Instance segmentation →it considers each item as a unique instance, segmenting them into different regions.

source: https://www.warrenphotographic.co.uk/11238-two-pomeranians-with-paws-over

Image segmentation is often mentioned in the same context of object detection (you can read more about object detection here). However, they address two different tasks.

With object detection, we aim at locating objects in a given image, building bounding boxes around them (which have spatial coordinates) and then classify the object they envelop.

On the other hand, with image segmentation, we aim at clustering together the image’s pixels…