We present an overview of various edge and line oriented approaches to contour detection
that have been proposed in the last two decades. By edge and line oriented we mean …

Automata models of learning systems introduced in the 1960s were popularized as learning
automata (LA) in a survey paper by Narendra and Thathachar (1974). Since then, there …

We describe a geometric-flow-based algorithm for computing a dense oversegmentation of
an image, often referred to as superpixels. It produces segments that, on one hand, respect …

A novel method is proposed for performing multilabel, interactive image segmentation.
Given a small number of pixels with user-defined (or predefined) labels, one can analytically …

Although deep models have greatly improved the accuracy and robustness of image
segmentation, obtaining segmentation results with highly accurate boundaries and fine …

In this correspondence, we develop a novel approach that provides effective and robust
segmentation of color images. By incorporating the advantages of the mean shift (MS) …

Networks of Learning Automata: Techniques for Online Stochastic Optimization is a
comprehensive account of learning automata models with emphasis on multiautomata …

Occlusion reasoning is a fundamental problem in computer vision. In this paper, we propose
an algorithm to recover the occlusion boundaries and depth ordering of free-standing …

Spectral clustering is a clustering method based on algebraic graph theory. It has aroused
extensive attention of academia in recent years, due to its solid theoretical foundation, as …

In a typical content-based image retrieval (CBIR) system, target images (images in the
database) are sorted by feature similarities with respect to the query. Similarities among …