Abstract

A real-world computer vision module must deal with a wide variety of environmental parameters. Object recognition, one of the major tasks of this vision module, typically requires a preprocessing step to locate objects in the scenes that ought to be recognized. Genetic algorithms are a search technique for dealing with a very large search space, such as the one encountered in image segmentation or object recognition. This work describes a technique for using genetic algorithms to combine the image segmentation and object recognition steps for a complex scene. The results show that this approach is a viable method for successfully combining the image segmentation and object recognition steps for a computer vision module. 1. INTRODUCTION A central task of the computer vision module is to recognize objects from images of the machine's environment. Navigation systems require the localization and recognition of landmarks or threats; robotic systems must find objects to manipulate; image re...

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