6 Mins Read

Introduction to Image Segmentation

Mitra Safari

August 20, 2022

Table of contents

Introduction to Image Segmentation

Applications of Image Segmentation

Introduction to Image Segmentation

Computer vision is a subfield of artificial intelligence, that gives us the ability to process digital images and videos to extract meaningful information using machine learning and deep learning. Image Classification, object detection, object tracking, and image segmentation are some of the processes we can perform on digital images using computer vision. We will discuss image segmentation in this article. In computer vision, image segmentation is the best choice when we are looking to differentiate between objects with the highest degree of accuracy.

What is Image Segmentation?

In addition to detecting the objects present in an image, Segmentation aims to determine where and how the detected objects are placed in the picture.

To tell the model what we are looking for, we annotate the image by drawing a polygon around every object in the image at a pixel level and labeling it. The resulting model then easily detects and labels objects in images. In the example image below, the segmentation model detects objects such as the wall, clock, laptop, people, and sofa in the picture.

Figure 1. (A) segmented image (B) original image

Types of Image Segmentation

Figure 2. (A) original image (B) semantic segmentation (C) instance segmentation (D) panoptic segmentation

1. Semantic segmentation

In Semantic Segmentation objects are only classified into predetermined classes, that’s to say if we have several of the same objects in the picture, all of them will be labeled as a class and there will be no clear distinction between them.

2. Instance segmentation

In this type of segmentation we differentiate between similar objects. Instance segmentation, recognizes each object in the image separately, and generates a mask for each object. This means that the model first focuses on the object type and then individually identifies each object’s instance.

3. Panoptic segmentation

Panoptic segmentation is a combination of Semantic and Instance segmentation, where each instance of an object is individually detected and labeled.

Applications of Image Segmentation

Image segmentation has important applications in various industries like Medical Imaging, Self-Driving Cars, Satellite Imaging, industrial inspection, etc.

1. Medical Imaging

Image segmentation can be used for tasks such as cancer cell segmentation or locating tumors and other pathologies. Image segmentation helps speed up diagnoses.

Figure 3. (A) Bone Tumor segmentation [3] (B) Coronary artery segmentation [4] (C) Pathology segmentation [5]

2. Self-Driving Cars

Self-driving cars have to identify roads, pedestrians, traffic signs, etc. to be able to execute appropriate commands and safely navigate to their destination. Image segmentation is therefore a key part of the software behind self-driving cars.

Figure4. Using Segmentation to give a Self-Driving car the ability to see [6]

3. Satellite Imaging

Image segmentation can precisely identify forests, mines, bodies of water, etc. in satellite images and track their changes over time.

Figure 5. Segmentation of satellite Earth imagery [7]

4. industrial inspection

Inspection and maintenance of industrial equipment is a very difficult and time-consuming task. Implementing Image Segmentation in the process can make failure detection significantly faster and safer.

Figure 6. Railroad track components inspection using segmentation [8]

Reference

1. https://labelbox.com/image-segmentation-overview

2. https://www.analyticsvidhya.com/blog/2021/03/introduction-to-image-segmentation-for-data-science/

3. https://www.mdpi.com/2075-4418/11/4/691/html

4. https://www.nature.com/articles/s41598-021-93889-z

5. https://medium.com/red-buffer/ai-in-computational-pathology-d05d8f9f3c03

6. https://studentsxstudents.com/using-semantic-segmentation-to-give-a-self-driving-car-the-ability-to-see-6c97425ec562?gi=bcdc3b1651f1

7. https://www.mdpi.com/2072-4292/8/4/329/pdf?version=1460636417

8. https://onlinelibrary.wiley.com/doi/abs/10.1111/mice.12625

Public

Ensemble Machine Learning

Ensemble machine learning is a powerful technique that leverages the strengths of multiple weak learning models, also known as...

Parisa Sabzeh

February 19, 2023

5 Mins Read

Public

Activation Functions in Neural Network

Activation functions are the main components of neural network nodes. This article examines the various types of activation functions...

Parisa Sabzeh

February 19, 2023

4 Mins Read

Public

Various Types of Regularization

Regularization is a technique used in Machine Learning and Deep Learning models to prevent overfitting. This paper introduces L1,...

Hamed Mohamadi

February 17, 2023

3 Mins Read

Public

Machine Learning Engineers Should Use Docker

Docker is a platform that enables developers to easily create, deploy, and run applications in containers, and has gained...

Hamed Mohamadi

February 17, 2023

4 Mins Read

Public

TPU, GPU, CPU: Which Is Better for Deep Learning?

In this paper, we compare the performance of CPU, GPU, and TPU processors to see which one is better...

Hamed Mohamadi

February 11, 2023

3 Mins Read

Public

The History of AI (part 2)

In the second part of a series of articles about the history of artificial intelligence, we look at important...

Parisa Sabzeh

January 28, 2023

3 Mins Read

Surfing on Categories

Subscribe to our newsletter and get the latest practical content.

You can enter your email address and subscribe to our newsletter and get the latest practical content. You can enter your email address and subscribe to our newsletter.

How does AIEX work?

Revolutionary Indsutry Transformation

Revolutionary Indsutry Transformation

Introduction to Image Segmentation

Introduction to Image Segmentation

What is Image Segmentation?

Types of Image Segmentation

1. Semantic segmentation

2. Instance segmentation

3. Panoptic segmentation

Applications of Image Segmentation

1. Medical Imaging

2. Self-Driving Cars

3. Satellite Imaging

4. industrial inspection

Reference

About

Contact Info

info@aiex.ai