What Is Image Segmentation?

Image segmentation is the technique and process of dividing an image into several specific regions with unique properties and proposing a target of interest. It is a key step from image processing to image analysis. The existing image segmentation methods are mainly divided into the following categories: threshold-based segmentation methods, region-based segmentation methods, edge-based segmentation methods, and specific theory-based segmentation methods. From a mathematical perspective, image segmentation is the process of dividing a digital image into disjoint regions. The process of image segmentation is also a labeling process, that is, assigning pixels that belong to the same area to the same number. ^[1]

Image segmentation

Image segmentation

There is no universal theory of image segmentation. With the development of many new theories and methods in various disciplines, many image segmentation methods combined with some specific theories and methods have appeared.

Machine vision

Face recognition

3. Fingerprint recognition

4. Traffic Control System

5. Locate objects (roads, forests, etc.) in satellite images

6. Pedestrian detection

7. Medical imaging, including:

(1) Localization of tumors and other pathologies

(2) Measurement of tissue volume

(3) Computer-guided surgery

(4) Diagnosis

(5) Customization of treatment plan

(6) Study of anatomical structure

There are many image segmentation algorithms for various purposes. There is no uniform solution to the problem of image segmentation. This technology is usually combined with the knowledge of related fields, so that the image segmentation problem in this field can be solved more effectively.

The research on image segmentation algorithms has a history of several decades. With the help of various theories, thousands of various types of segmentation algorithms have been proposed so far. Although people have done a lot of research work on image segmentation. But because there is no universal segmentation theory, the segmentation algorithms that have been proposed are mostly for specific problems, and there is no universal segmentation algorithm suitable for all images. However, it can be seen that image segmentation methods are developing in a faster and more accurate direction, and breakthroughs and progress will be continuously achieved through the combination of various new theories and new technologies.