Image segmentation using Gaussian curvature
Neelima Shrikhande, Sripriya Ramaswamy · Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE · 1995
One of the central problems of computer vision is segmentation of images into salient features such as edges and surfaces. Different kinds of similarity criteria can be used to group related pixels together. One such criterion is the curvature of surfaces in an image of a multiobject scene that contains several objects with different shapes. In practice, however, curvature is difficult to calculate because small amount of noise can cause large amounts of errors in calculations of first and second derivatives. In this paper, we use a discrete approximation of Gaussian curvature that is efficient to compute. The approximation is used to segment the image into individual surfaces. Both synthetic and real images have been tested. Results appear quite encouraging.© (1995) COPYRIGHT SPIE--The International Society for Optical Engineering. Downloading of the abstract is permitted for personal use only.