Attention-aware color theme extraction for fabric images

Author:

Liu Shiguang12,Jiang Yaxi1,Luo Huarong1

Affiliation:

1. School of Computer Science and Technology, Tianjin University, P.R. China

2. Tianjin Key Laboratory of Cognitive Computing and Application, P.R. China

Abstract

Color configuration plays an important role in art, design, and communication, which can influence the user’s experiences, feelings, and psychological well-being. It is laborious to manually select a color theme from scratch for handling large batches of images. Alternatively, it can inspire designers’ creations and save their time as well by leveraging the color themes in existing art works (e.g. fabric, paintings). However, it is challenging to automatically extract perceptually plausible color themes from fabric images. This paper presents a new automatic framework for extracting color themes from fabric images. A saliency map is built to help recognize the visual attention regions of the input image. Since the saliency map separates the image into visual attention regions (foreground) and non-visual attention regions (background), we respectively compute the dominant colors of these two regions, and merge them to form the initial target color theme based on certain rules. The dominant colors are extracted, accounting for the characteristics of the fabric and hue distributions of fabric images so as to acquire visually plausible results. Our method can be used to transfer colors between two fabric images for fabric color design. We tested our method thoroughly with various fabric images (e.g. cotton, silk, and linen) with different texture patterns (e.g. plain and twill). Experiments show that our method is more efficient and can generate more visually plausible results than state-of-the-art algorithms.

Publisher

SAGE Publications

Subject

Polymers and Plastics,Chemical Engineering (miscellaneous)

Cited by 26 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3