DESIGN ELEMENTS EXTRACTION BASED ON UNSUPERVISED SEGMENTATION AND COMPACT VECTORIZATION

Hong Qu, Yanghong Zhou, K. P. Chau, P. Y. Mok

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

Abstract

Repeated design elements are abundant and ubiquitous in decorative patterns, which are now widely used in the process of design for objects, artworks and images found in our living environment. Extraction of repeated design elements from images of existing decorative patterns benefits understanding design, extracting compressed information for subsequent operation, e.g., design generation and vectorization. The early methods based on hand-crafted features were computationally inefficient and less accurate. Most deep learning (DL) based methods focus on natural environment images and are difficult to generalize to decorative images. Besides, DL-based methods require massive datasets with instance-level annotations, which are labor-intensive and hard to get. This paper proposes a novel scheme for design element extraction and vectorization. First of all, unsupervised segmentation is proposed to extract repeated design elements from images of unknown artworks without human assistance. We then distill the color information of the extracted repeated element based on statistics reflected in the color histogram of the input artwork. We develop an algorithm to remove redundant information extracted from images in order to get a compact vectorization result, reusable design element in vector format, at the end. To validate the proposed scheme, we conducted several experiments and the result demonstrated the effectiveness of our scheme and its potential for design generation application.

Original languageEnglish
Title of host publication16th International Conference on Computer Graphics, Visualization, Computer Vision and Image Processing, CGVCVIP 2022, 8th International Conference on Connected Smart Cities, CSC 2022, 7th International Conference on Big Data Analytics, Data Mining and Computational Intelligence, BigDaCI 2022, and 11th International Conference on Theory and Practice in Modern Computing, TPMC 2022 - Held at the 16th Multi Conference on Computer Science and Information Systems, MCCSIS 2022
PublisherIADIS Press
Pages78-84
Number of pages7
ISBN (Electronic)9789898704429
Publication statusPublished - Jul 2022
Event16th International Conference on Computer Graphics, Visualization, Computer Vision and Image Processing, CGVCVIP 2022, 8th International Conference on Connected Smart Cities, CSC 2022, 7th International Conference on Big Data Analytics, Data Mining and Computational Intelligence, BigDaCI 2022, and 11th International Conference on Theory and Practice in Modern Computing, TPMC 2022 - Held at the 16th Multi Conference on Computer Science and Information Systems, MCCSIS 2022 - Lisbon, Portugal
Duration: 19 Jul 202222 Jul 2022

Publication series

Name16th International Conference on Computer Graphics, Visualization, Computer Vision and Image Processing, CGVCVIP 2022, 8th International Conference on Connected Smart Cities, CSC 2022, 7th International Conference on Big Data Analytics, Data Mining and Computational Intelligence, BigDaCI 2022, and 11th International Conference on Theory and Practice in Modern Computing, TPMC 2022 - Held at the 16th Multi Conference on Computer Science and Information Systems, MCCSIS 2022

Conference

Conference16th International Conference on Computer Graphics, Visualization, Computer Vision and Image Processing, CGVCVIP 2022, 8th International Conference on Connected Smart Cities, CSC 2022, 7th International Conference on Big Data Analytics, Data Mining and Computational Intelligence, BigDaCI 2022, and 11th International Conference on Theory and Practice in Modern Computing, TPMC 2022 - Held at the 16th Multi Conference on Computer Science and Information Systems, MCCSIS 2022
Country/TerritoryPortugal
CityLisbon
Period19/07/2222/07/22

Keywords

  • Image Understanding
  • Localization
  • Unsupervised Segmentation
  • Vectorization

ASJC Scopus subject areas

  • General Computer Science

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