Perception-based image classification

Pattern classification methodologies are present in many systems that we depend on daily. In these systems, classes are created based on human perception of the objects being classified. Thus, it is important to have systems that accurately model human perception. Near set theory provides a framework for measuring the similarity of objects based on features that describe them in much the same way that humans perceive objects. In this paper, we show that the near set approach can be used to classify images. Further, the results presented here suggest that the near set approach can be used in any image classification system. The contribution of this article is a perception based classification of images using near sets.