Instance segmentation vs. semantic segmentation

Segmentation refers to the process of dividing an image into distinct regions or objects based on certain criteria, such as color, texture, or shape. It enables the isolation and analysis of specific regions or objects, making it essential in applications like object tracking, video surveillanceIt is an act of capturing activities in a specific area for observation purposes using cameras., geographical image analysisIt means examining remote sensing images collected by satellites or drones of specific locations., and many more. In this Answer, we’ll discuss two types of segmentation:

• Semantic segmentation

• Instance segmentation

Semantic segmentation

Semantic segmentation segments the image regions corresponding to different objects and classifies them. This type of segmentation performs pixel-level classification, classifying each pixel within an image into predefined classesFor example: Person, animal, and bird. It aims to provide a detailed understanding of the objects and regions present in an image by assigning a semantic label to every pixel. Each pixel in the image is associated with a label representing the object or category to which it belongs, resulting in a comprehensive segmentation map.

A segmentation map is the visual output of the semantic segmentation process. It is a mask covering the entire image, with each pixel color-coded or labeled according to its semantic class. This provides a pixel-level understanding of an image. The dimensions of a segmentation map are the same as the original input image. Below is an example of a segmentation map of an image:

In the example above, multiple pixels in the image corresponding to the same object are labeled with the same semantic labels. These semantic labels are mapped to distinct colors, which serve to visualize and distinguish the various objects present in the image.

Semantic segmentation is used in various domains, including autonomous drivingA robotic vehicle operating without any human intervention using various sensors and AI models., medical image analysisExtracting information from medical images and interpreting it for diagnosis and treatment planning., and object recognitionIdentifying objects in a frame.. You can find information on the complete process of semantic segmentation in this Answer.

Instance segmentation

Instance segmentation is used to segment every individual object recognized in the image. This type of segmentation assigns distinct labels for separate instances of objects sharing the same class. Moreover, it combines the capabilities of semantic segmentation and object detection by effectively distinguishing and outlining each object with bounding boxes.

In the example above, each class is distinguished by a boundary box. Then, each instance is segmented by a unique color, along with its probabilities denoting its association with a specific object. Instance segmentation is used in various domains, including robotics, traffic control systems, agriculture[object Object], and many more.

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