GA-based object recognition in a complex noisy environment

Abstract

This paper describes a method for object recognition in a complex noisy environment based on the genetic algorithm (GA). A small object is represented by their binary edges. A fitness function is constructed by the shape of an object in combination with its frame model to search for the position and orientation of the target in the input image. In order to enhance the orientation function of the fitness function, some preprocessing operations have been done. The simulation result shows that the method presented is effective and has great practical value.