Image segmentation

Image segmentation refers to partitioning an image into multiple segments to simplify analysis. It is a core technique in digital image processing and computer vision. Key aspects:

Segments represent distinct objects or regions of interest.
Similar pixels are grouped based on visual attributes like color, intensity, texture.
Results in a set of contours, pixels, or shapes outlining segments.
Used for localization, object detection, boundary marking.
Classes of methods include thresholding, clustering, edge detection.

Applications include:

Isolating objects from backgrounds in photos.
Identifying structures of interest in medical scans.
Demarcating roads, buildings, fields in satellite imagery.
Robot vision and self-driving vehicles.

Challenges involve handling noise, occlusion, blurring, and illumination variance. Deep learning and neural nets now enable segmentation with high accuracy.

Overall, image segmentation provides fundamental region-based image analysis benefiting many computer vision tasks.