Object Segmentation

In computer vision and image processing, object segmentation is the process of partitioning a digital input into multiple object segments.

Object Segmentation Tasks and Types

Object Segmentation can be classified into three main groups on the basis of the informationthey deliver: they can be panoptic, instance, and semantic segmentation, with each of them having its own importance. Here we will explore each of them briefly.

Object Segmentation

In computer vision and image processing, object segmentation is the process of partitioning a digital input into multiple object segments.

Object Segmentation Tasks and Types

1. Semantic Segmentation

Semantic Segmentation helps specify the form, size, and shape of the objects as well as their location. It is used in such cases where a model most definitely needs to know whether an image actually has the object of interest or not and what sections of visual input do not belong to the object. Pixels that belong to a particular class are classified without taking any other information or context into consideration.

2. Instance Segmentation

Instance Segmentation keeps the track of the shape, size, number, location, and presence ofobjects in an image. The primary goal is to grasp the image in full accuracy with every pixel. Hence, the “instances” are what the pixels are based on instead of the classes to segregate similar objects or overlapping based on their boundaries including when it comes to image segmentation python.

3. Panoptic Segmentation

The most informative task in Object Segmentation is undoubtedly the panoptic segmentation as it blends both instance and semantic segmentation, providing a lot of information for modern ML algorithms or for object segmentation deep learning.

Computer Vision applications that use Object Segmentation

Object Segmentation can be seen applied in various IT sections. Some of them are the following:

Geospatial application (semantic segmentation)
Autonomous vehicles (instance segmentation)
Geo-sensing application (semantic segmentation)
Precision agriculture (non-instance segmentation)
E-commerce fashion application (instance segmentation)
Cancer cell identification (instance segmentation)

Now we have a fair share of an idea of how and where object segmentation is playing its key roles in the fields of Image Segmentation and Computer Vision. And that’s good knowledge to have especially with respect to the object segmentation tasks done by deep learning and machine learning.