Texture segmentation for seam carving

Gilor Raz, Ron Shmueli, Eyal Katz

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations

Abstract

This paper analyzes the relationships between texture characteristics of an image and seam-carving (SC) algorithm for image retargeting (resizing). SC is a smart image content aware algorithm. The algorithm, changes the aspect ratio of an image while keeping the 'important' objects untouched. Based on a subjective test, we combine between an image's characteristics and a saliency map which provides best results. Furthermore, in order to determine the significance of these results, we use principal component analysis (PCA) statistical method, which identifies those relationships in the subjective test's results. Finally, we present a novel saliency map for SC algorithm. This saliency map is based on a new classification model, which uses statistical connections between neighboring pixels and significantly reduces the level of distortion along the process, providing optimal preservation of important objects within the image.

Original languageEnglish
Title of host publication2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016
PublisherInstitute of Electrical and Electronics Engineers
ISBN (Electronic)9781509021529
DOIs
StatePublished - 4 Jan 2017
Externally publishedYes
Event2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016 - Eilat, Israel
Duration: 16 Nov 201618 Nov 2016

Publication series

Name2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016

Conference

Conference2016 IEEE International Conference on the Science of Electrical Engineering, ICSEE 2016
Country/TerritoryIsrael
CityEilat
Period16/11/1618/11/16

Keywords

  • image QOS
  • image retargeting
  • saliency map
  • seam carving
  • subjective tests

ASJC Scopus subject areas

  • Computer Science Applications
  • Hardware and Architecture
  • Artificial Intelligence
  • Computer Networks and Communications
  • Electrical and Electronic Engineering

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