Image Segmentation
Image Segmentation is an crucial task in computer vision for dividing an image into meaningful segments or regions. The divided segments can correspond to individual objects, parts of objects or regions with similar characteristics. This image segmentation process can break down an image into meaningful building blocks to help computer to identify and understand the content.
The main goal of image segmentation is to divide an image into distinct segments or regions which are related to meaningful objects, regions or even individual pixels.
There are 2 main types of image segmentation:
- Semantic Segmentation: Semantic segmentation in computer vision involves assigning a class label to each individual pixel in an image. Each pixel in an image is categorized and assigned a label based on the object it belongs. When an semantic segmentation is done on an image the output is a ‘segmentation map’ where each pixel’s color represents its class.
- Instance Segmentation: Instance segmentation delves into the image at a more granular level by identifying and delineating each individual instance of those objects. It is something like, as an example of, having different coloured cats in an image. Another good example could be, imagine a group photo of students. Semantic segmentation labels everyone as ‘person’, and instance segmentation would identify and outline each individual person in the group photo.
There is also another segmentation type called Panoptic Segmentation which combines both semantic and instance segmentation to provide a complete understanding of every pixel in the image.
Image segmentation process is used in various applications like medical imaging, to identify tumours or organ health and in autonomous driving to assist in distinguishing between road, vehicles, and pedestrians.
Computer Vision Tasks
Computer vision is a branch of artificial intelligence that helps computers understand and analyze visual data from digital images, videos, and similar visual inputs. Using digital visual data obtained from various sources, we can teach computers to detect and interpret visual objects. It also plays a critical role in areas such as image recognition and object detection. There are many different tasks that computer vision can perform. In this article, we will discuss computer vision tasks in detail.
Table of Content
- What are computer vision tasks?
- Image Classification
- Object Detection
- Image Segmentation
- Face and Person Recognition
- Edge Detection
- Image Restoration
- Feature Matching
- Scene Reconstruction
- Video Motion Analysis
- Conclusion:
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