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Hierarchical object recognition from a 2D image using a genetic algorithm

A new approach for object recognition is proposed. Many object recognition methods have been studied. Most of them required one precise object model for recognizing only one object. Accordingly, it is necessary to prepare a model for only one object in advance. Moreover, it is difficult to make the precise model, and a long computational time is necessary to match it with the input image. In this paper, a hierarchical object recognition method using a genetic algorithm (GA) is proposed. GAs can provide robust search in complex spaces. Therefore GAs are suitable for object recognition problems which have many parameters. In the proposed method, the input image is first simplified, and then the simplified image is matched with a fundamental model. By means of the hierarchical method, a precise object model is not necessary, and only one fundamental model represents the objects which belong to the same category.