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PointFlow: A Model for Automatically Tracing Object Boundaries and Inferring Illusory Contours

  • Fang YangEmail author
  • Alfred M. Bruckstein
  • Laurent D. Cohen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10746)

Abstract

In this paper, we propose a novel method for tracing object boundaries automatically based on a method called “PointFlow” in image induced vector fields. The PointFlow method comprises two steps: edge detection and edge integration. Basically, it uses an ordinary differential equation for describing the movement of points under the action of an image-induced vector field and generates induced trajectories. The trajectories of the flows allow to find and integrate edges and determine object boundaries. We also extend the original PointFlow method to make it adaptable to images with complicated scenes. In addition, the PointFlow method can be applied to infer certain illusory contours.

We test our method on real image dataset. Compared with the other classical edge detection and integration models, our PointFlow method is better at providing precise and continuous curves. The experimental results clearly exhibit the robustness and effectiveness of the proposed method.

Keywords

Automatically tracing object boundaries Induced vector field PointFlow Differential equations Illusory contours 

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Copyright information

© Springer International Publishing AG, part of Springer Nature 2018

Authors and Affiliations

  • Fang Yang
    • 1
    Email author
  • Alfred M. Bruckstein
    • 2
  • Laurent D. Cohen
    • 1
  1. 1.CEREMADE, CNRS, UMR 7534, Université Paris Dauphine, PSL Research UniversityParisFrance
  2. 2.Computer Science DepartmentTechnion – IITHaifaIsrael

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