Qualitative Recognition of Aircraft in Perspective Aerial Images

Abstract

Recognition of aircraft in complex, perspective aerial imagery is difficult because of occlusion, shadow, cloud cover, haze, seasonal variations, clutter and various forms of image degradation. This chapter describes a system for aircraft recognition that addresses some of these issues. The recognition system uses a hierarchical object model database that includes models represented using advance concepts to geometric entities. It involves three key processes: (a) The qualitative object recognition process is responsible for model-based symbolic feature extraction and generic object recognition; (b) The refocused matching and evaluation process accesses deeper levels of the database hierarchy with input from (a) to refine the extracted features and to perform more specific classification; and (c) the primitive feature extraction process regulates the extracted features based on their saliency and interacts with (a) and (b). Experimental results showing the qualitative recognition of aircraft in perspective, aerial images are presented.