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.
Keywords: Image segmentation, Feature classification, Machine Learning types.