Edge detection algorithm for omnidirectional images, based on superposition laws on Blach’s sphere and quantum entropy

Abstract

This paper presents an edge detection algorithm for omnidirectional images based on superposition law on Bloch’ s sphere and quantum local entropy. Omnidirectional vision system has become an essential tool in computer vision, due to its large field of view. However, classical image processing algorithms are not suitable to be applied directly on this type of images without taking into account the spatial information around each pixel. To show the performance of the proposed method, a set of experimentation was done on synthetic and real images devoted to agriculture applications. Later, Fram & Deutsh criterion has been adopted to evaluate its performance against three algorithms proposed in the literature and developed for omnidirectional images. The results show a better performance in term of edge quality, edge community and sensibility to noise.