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Article

An Automated System for Garment Texture Design Class Identification

Institute of Information Technology, University of Dhaka, Dhaka 1000, Bangladesh
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Academic Editor: Pedro Alonso Jordá
Computers 2015, 4(3), 265-282; https://doi.org/10.3390/computers4030265
Received: 15 June 2015 / Revised: 7 September 2015 / Accepted: 9 September 2015 / Published: 17 September 2015
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
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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. https://doi.org/10.3390/computers4030265

AMA Style

Dey EK, Tawhid MNA, Shoyaib M. An Automated System for Garment Texture Design Class Identification. Computers. 2015; 4(3):265-282. https://doi.org/10.3390/computers4030265

Chicago/Turabian Style

Dey, Emon K.; Tawhid, Md. N.A.; Shoyaib, Mohammad. 2015. "An Automated System for Garment Texture Design Class Identification" Computers 4, no. 3: 265-282. https://doi.org/10.3390/computers4030265

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