An extension of min/max flow framework

  • Authors:

  • Hongchuan Yu;Mohammed Bennamoun;Chin-Seng Chua

  • Affiliations:

  • The Media School, Bournemouth University, Poole, UK;School of Computer Science and Software Engineering, University of Western Australia, Perth, WA 6009, Australia;School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore

  • Venue:
  • Image and Vision Computing
  • Year:
  • 2009

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Abstract

In this paper, the min/max flow scheme for image restoration is revised. The novelty consists of the following three parts. The first is to analyze the reason of the speckle generation and then to modify the original scheme. The second is to point out that the continued application of this scheme cannot result in an adaptive stopping of the curvature flow. This is followed by modifications of the original scheme through the introduction of the Gradient Vector Flow (GVF) field and the zero-crossing detector, so as to control the smoothing effect. Our experimental results with image restoration show that the proposed schemes can reach a steady state solution while preserving the essential structures of objects. The third is to extend the min/max flow scheme to deal with the boundary leaking problem, which is indeed an intrinsic shortcoming of the familiar geodesic active contour model. The min/max flow framework provides us with an effective way to approximate the optimal solution. From an implementation point of view, this extended scheme makes the speed function simpler and more flexible. The experimental results of segmentation and region tracking show that the boundary leaking problem can be effectively suppressed.