A genetic algorithm for aligning object shapes

摘要

Recently, the use of dominant points for boundary alignment has been widely adopted in a lot of object recognition techniques. The success of these approaches is highly dependent on the availability of a set of spatially matched dominant point pairs on the scene and the reference contours. This criteria, however, is difficult to attain in practice as the distribution of dominant points are often found to change with the pose and size of the object images that are grabbed under different camera position. In this paper, a novel technique based on the genetic algorithm for searching the best alignment between contours of near-planar objects is reported. The method is more efficient and robust than the dominant point approaches, and is capable of arriving at the optimal solution instead of being trapped in the local minimum where only partial alignment of the contours is achieved. Experimental results obtained with the proposed scheme are encouraging which demonstrate the feasibility of the approach.