Genetic Algorithm Approach to Edge Detection for Dental X-ray Image Segmentation
N. Senthilkumaran · International journal of advanced research in computer science and electronics engineering · 2012
Genetic Algorithm is an optimization solver, which does an analogy to Darwin evolution by combining mutation, crossover and selection step. One of the biggest advantages of Genetic Algorithm is its ability to find a global optimum. The X-ray data set, which consists of an image and its expected edge features, is used for training by the GA. Image edge detection refers to the extraction of the edges in a digital image. An edge is a boundary between the object and its background. Edge detection is most common approach to detect discontinuity in an image. Edge detection is a process to identify points in an image where discontinuities or sharp changes in intensity occur. This process is crucial to understanding the content of an image and has its applications in image analysis and machine vision. Edge detection is usually applied in initial stages of computer vision applications. In this paper, the main aim is to study the edge detection method for Dental X-ray image segmentation based on a genetic algorithm approach.