Contour detection by image analogies

Slimane Larabi, Neil Robertson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

In this paper we deal only contour detection based on image analogy principle which has been used in super resolution images, texture, curves synthesis and interactive editing. Human is able to hand drawn best outlines that may considered as benchmarks for contour detection and image segmentation algorithms. Our goal is to model this expertise and to pass on it at the computer for contour detection. Giving a reference image where outlines are drawn by human, we propose a method based on the learning of this expertise to locate outlines of a query image in the same way that is done for the reference. Experiments are conducted on different data sets and the obtained results are presented and discussed.
Original languageEnglish
Title of host publicationAdvances in Visual Computing
Subtitle of host publicationLecture Notes in Computer Science
Place of PublicationHiedelberg
PublisherSpringer
Pages430
Number of pages439
Volume7432
Edition2012
ISBN (Electronic)978-3-642-33191-6
ISBN (Print)978-3-642-33190-9
DOIs
Publication statusPublished - 16 Jul 2012

Keywords

  • Computer vision

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  • Cite this

    Larabi, S., & Robertson, N. (2012). Contour detection by image analogies. In Advances in Visual Computing: Lecture Notes in Computer Science (2012 ed., Vol. 7432, pp. 430). Springer. https://doi.org/10.1007/978-3-642-33191-6_42