Abstract

Image is an important medium to express information easily. This paper deals with the content of image segmentation with machine learning. Segmentation is the process of extracting the information required from the image. Machine learning is the process that helps to classify to obtain good results. A number of algorithms are designed for the segmentation process. The algorithms are selected based on the application. Quality segmentation can be applied if the algorithm is fixed at the application level. Standalone methods can be used for real-time applications. Schematic segmentation is one of the best techniques used for segmenting images. Machine learning combines basic techniques to produce good results. The algorithms vary for different input images like MRI, CT Scans, Colour images, etc. Algorithms like k-mean clustering are mostly used in processing. Many problems occur in segmentation which can be removed by Bayesian architectures. The usage of machine learning improves accuracy and efficiency. Labeling, training and testing are some of the methods used in segmentation through machine learning.