Segmentation of digital images by an algorithm using the K-means clustering model

Abstract

Image fragmentation plays an important role in Computer Vision. It is: dividing the digital image into objective regions, by identifying digital regions that have similar characteristics from non-similar regions. The problem of image fragmentation is one of the problems in which the optimal solution is used, in this The research was using the optimal solution method that depends on the K-means clustering algorithm to find the optimal image segmentation.These different proposed methods have been tested using grayscale and color images of different sizes, and these methods have been compared.The achievement of the grouping algorithm and its success in solving The problem of image segmentation. The work included reliance on the method of classification using segmentation, and the test results showed its high efficiency in classifying image regions. The system of image segmentation using grouping has the ability to develop and classify, it can classify a variety of scenarios that include any application, as well as it has the ability to learn,