Model based object recognition

Abstract

Machine vision or computer vision is the study of methods that machines understand multi-dimensional data, such as images or a sequence of images, three-dimensional volume data, and single to multi-variable signals. Whereas computer vision is mainly focused on machine-based image processing, machine vision most often requires also digital input/output devices and computer networks to control other manufacturing equipment such as robotic arms. Machine Vision is a subfield of engineering that encompasses computer science, optics, mechanical engineering, and industrial automation. Many fields can be related to machine vision, such as mathematics, physics, artificial intelligence, image processing, biology, signal processing, etc.; the application of this field is diverse. In this paper, we propose a robust and efficient system for model based object recognition based on wavelets and multiresolution analysis. This framework is suitable for autonomous vehicle navigation. Since our approach is simple and effective, it can be used in real time processing or expanded for more complex applications.