ABSTRACT

Image segmentation is to partition an image into meaningful regions with respect to a particular application. Object recognition is the task of finding a given object in an image or video sequence. This paper discusses the interaction between image segmentation and object recognition in the framework of the Expectation-Maximization (EM) algorithm. Threshold is image processing technique for converting grayscale or color image to a binary image based upon a threshold value. The OTSU method is one of the applied methods of image segmentation in selecting threshold automatically for its simple calculation and good adaptation. Genetic Algorithms (GAs) tries to find structure in data that might seem random, or to make a seemingly unsolvable problem more or less 'solvable'. In this paper a synergy between Image segmentation and object recognition using EM algorithm, OSTU and GA.