Recognition of occluded objects by a genetic algorithm

Abstract

In this paper we present a new algorithm to extract and locate partially visible objects from a 2D image. For each model object, the algorithm cuts a prominent fragment front its boundary. Next, using a genetic algorithm, the algorithm finds an image fragment with the best match to the model fragment from match boundary of the image objects. As a result, the corresponding model is extracted and located from the image. The proposed algorithm can be used for the recognition of objects whose scales, rotations and translations are unknown. In addition, the algorithm can locate objects whose boundaries are distorted.