Open AccessApplication of Computer Vision in T-Shirt Dimensions Measurement
Author(s) -
Ngoc-Bich Le,
Thi-Thu-Hien Pham,
Quoc-Hung Phan,
Narayan C. Debnath,
Ngoc-Huan Le
Publication year - 2022
Publication title -
eai endorsed transactions on industrial networks and intelligent systems
Language(s) - English
Resource type - Journals
ISSN - 2410-0218
DOI - 10.4108/eetinis.v9i31.707
Subject(s) - image processing , computer science , measure (data warehouse) , divergence (linguistics) , artificial intelligence , computer vision , productivity , replication (statistics) , digital image processing , image (mathematics) , pattern recognition (psychology) , data mining , mathematics , statistics , linguistics , philosophy , macroeconomics , economics
This paper presents a solution to automatically measure the T-shirt dimensions in the garment industry. To address this goal, the paper focuses on utilizing image processing to determine the T-shirt's dimensions. The processing algorithm was provided along with the proposed recognition regions novel approach that was expected to deliver faster processing speed and enhance accuracy. The feasibility was demonstrated by characterizing the accuracy and processing speed. Specifically, five distinctive dimensions were successfully identified and measured; with the replication of 30, the discrepancy varies from 0.095% (for chest) to 2.088% (for collar). The divergence is insignificant compared with the granted tolerances. Finally, the processing time and the mechanical structure of the system deliver productivity of 22 products/minute which is approximately 10 times more rapidly than manual measurement (25 seconds).