| Title |
An intelligent solution for automatic garment measurement using image recognition technologies / |
| Authors |
Paulauskaite-Taraseviciene, Agne ; Noreika, Eimantas ; Purtokas, Ramunas ; Lagzdinyte-Budnike, Ingrida ; Daniulaitis, Vytautas ; Salickaite-Zukauskiene, Ruta |
| DOI |
10.3390/app12094470 |
| Full Text |
|
| Is Part of |
Applied sciences.. Basel : MDPI. 2022, vol. 12, iss. 9, art. no. 4470, p. 1-17.. ISSN 2076-3417 |
| Keywords [eng] |
segmentation ; UNet ; garment size detection ; edge detection ; key points |
| Abstract [eng] |
Global digitization trends and the application of high technology in the garment market are still too slow to integrate, despite the increasing demand for automated solutions. The main challenge is related to the extraction of garment information-general clothing descriptions and automatic dimensional extraction. In this paper, we propose the garment measurement solution based on image processing technologies, which is divided into two phases, garment segmentation and key points extraction. UNet as a backbone network has been used for mask retrieval. Separate algorithms have been developed to identify both general and specific garment key points from which the dimensions of the garment can be calculated by determining the distances between them. Using this approach, we have resulted in an average 1.27 cm measurement error for the prediction of the basic measurements of blazers, 0.747 cm for dresses and 1.012 cm for skirts. |
| Published |
Basel : MDPI |
| Type |
Journal article |
| Language |
English |
| Publication date |
2022 |
| CC license |
|
