ASOD: Arbitrary shape object detection

Arbitrary shape object detection, which is mostly related to computer vision and image processing, deals with detecting objects from an image. In this paper, we consider the problem of detecting arbitrary shape objects as a clustering application by decomposing images into representative data points, and then performing clustering on these points. Our method for arbitrary shape object detection is based on COMUSA which is an efficient algorithm for combining multiple clusterings. Extensive experimental evaluations on real and synthetically generated data sets demonstrate that our method is very accurate and efficient.

► We propose a novel technique for detecting objects with arbitrary shapes. ► Our technique is based on clustering methodology. ► ASOD produces better results than segmentation on real and artificial data sets. ► Experimental evaluations demonstrate that ASOD is very accurate and efficient.