A Review on Image Segmentation Techniques and Its Recent Applications

The technique of attaching a name to each component in a picture so that elements with much the same label have certain visual qualities (pixels, colours, values, patterns, and other features of the image) is known as image segmentation. The output of image segmentation is a series of fragments or patterns taken from the image that collectively cover the full picture. After segmenting an image, classification detects classes in an image on the basic of similarities and differences between detected segments. These two tools together are doing wonders in better object detection in images. Big world has big data, and this big data need robust algorithms for understanding images without a human. This paper summarises the techniques of image segmentation and classification based on their efficiency. Finally, a comparison table shows who performed it better.