Chunk-based matching of images for ATR

摘要

This paper presents the results of an enhancement to the image matching component of an automatic target recognition (ATR) system that improves the ability to handle variations and articulations within a given class of targets. This method is based on chunking of an image and can be applied to any image matching system that uses templates to match against a given input image. Using information theoretical measures, templates are divided into sub-parts, called chunks. These chunks are scored individually against corresponding parts of an input image. Sub-part scoring adds the ability to distinguish poorly matching areas of the target from those that match well. If a very small set of chunks score significantly worse than the other chunks then the poor-scoring chunks may be discarded. This increases the scores of an input image that is of the same class but there is little or no effect on the score of an input image that is of another class.