Next Article in Journal
Hop-by-Hop Worm Propagation with Carryover Epidemic Model in Mobile Sensor Networks
Previous Article in Journal
Optimal Elbow Angle for Extracting sEMG Signals During Fatiguing Dynamic Contraction
Article Menu

Export Article

Open AccessArticle
Computers 2015, 4(3), 265-282; doi:10.3390/computers4030265

An Automated System for Garment Texture Design Class Identification

Institute of Information Technology, University of Dhaka, Dhaka 1000, Bangladesh
*
Author to whom correspondence should be addressed.
Academic Editor: Pedro Alonso Jordá
Received: 15 June 2015 / Revised: 7 September 2015 / Accepted: 9 September 2015 / Published: 17 September 2015
View Full-Text   |   Download PDF [1714 KB, uploaded 17 September 2015]   |  

Abstract

Automatic identification of garment design class might play an important role in the garments and fashion industry. To achieve this, essential initial works are found in the literature. For example, construction of a garment database, automatic segmentation of garments from real life images, categorizing them into the type of garments such as shirts, jackets, tops, skirts, etc. It is now essential to find a system such that it will be possible to identify the particular design (printed, striped or single color) of garment product for an automated system to recommend the garment trends. In this paper, we have focused on this specific issue and thus propose two new descriptors namely Completed CENTRIST (cCENTRIST) and Ternary CENTRIST (tCENTRIST). To test these descriptors, we used two different publically available databases. The experimental results of these databases demonstrate that both cCENTRIST and tCENTRIST achieve nearly about 3% more accuracy than the existing state-of-the art methods. View Full-Text
Keywords: texture descriptor; garment categories; tCENTRIST; cCENTRIST; garment trend identification texture descriptor; garment categories; tCENTRIST; cCENTRIST; garment trend identification
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Dey, E.K.; Tawhid, M.N.A.; Shoyaib, M. An Automated System for Garment Texture Design Class Identification. Computers 2015, 4, 265-282.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Computers EISSN 2073-431X Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top