Image Segmentation is the process of dividing an image into multiple segments or regions. It is used to identify objects and boundaries in an image.
Image segmentation is the process of dividing an image into multiple segments, or regions, that each contain pixels with similar characteristics. It is a form of image analysis that is used to identify objects and boundaries in digital images. Image segmentation is used in a variety of applications, including medical imaging, satellite imagery analysis, and object recognition.
The goal of image segmentation is to partition an image into meaningful regions that can be used for further analysis. This is done by grouping pixels that have similar characteristics, such as color, texture, and intensity. The process of segmentation involves identifying the boundaries between objects in an image and assigning each pixel to a particular region.
Image segmentation can be performed using a variety of techniques, including thresholding, clustering, region growing, and edge detection. Thresholding is a simple technique that assigns each pixel to a region based on its intensity value. Clustering is a more complex technique that groups pixels based on their similarity. Region growing is a technique that starts with a seed point and then grows the region by adding pixels that are similar to the seed point. Edge detection is a technique that identifies boundaries between objects in an image.
Image segmentation is an important step in many image processing tasks, such as object recognition, image classification, and image registration. It is also used in medical imaging to identify tumors, organs, and other structures. Image segmentation can also be used to improve the accuracy of image analysis tasks, such as object detection and tracking.