EVOLUTION OF IMAGE SEGMENTATION METHODS

It’s always fascinating to know how machines does the processing that humans do all the time using senses with high speed and accuracy. Image segmentation is a crucial task in computer vision and image processing, with numerous segmentation algorithms being found in the literature. It has important applications in scene understanding, medical image analysis, robotic perception, video surveillance, augmented reality, and image compression, among others. This paper discusses the evolution of methods used by machines for image segmentation. This research compares various methods for image segmentation and finds out the better one. This paper mainly concentrates on CNN based image segmentation method. Implementation and results of Faster R-CNN algorithm are provided.