Focused color intersection with efficient searching for object extraction

摘要

We propose focused color intersection with efficient searching for identifying and extracting the objects in a complex scene based on color similarity. The method matches the models against different parts of a scene, called focus regions, using normalized color histogram intersection. The best matching focus region is determined by an efficient search strategy employing upper bound pruning. This search strategy, called active search, concentrates its effort on parts of the scene having high similarity with the object. Consequently, it achieves a large reduction in computational effort without sacrificing accuracy. An efficient algorithm for evaluating the color histogram intersection between a model and a focus region is also given. Experiments conducted demonstrate that multiple known objects in complex scenes can be extracted by this process. The method is stable against scale changes, two-dimensional rotation, moderate changes in shape and partial occlusion.