Garment Image Retrieval based on Grab Cut Auto Segmentation and Dominate Color Method
Publié en ligne: 15 juil. 2022
Pages: 573 - 584
Reçu: 08 févr. 2022
Accepté: 07 avr. 2022
DOI: https://doi.org/10.2478/amns.2022.2.0042
Mots clés
© 2023 Hong Liu et al., published by Sciendo
This work is licensed under the Creative Commons Attribution 4.0 International License.
Targeted at the harmful effects of garment image retrieval at present, a new approach of garment image retrieval featured in satisfactory performance is proposed. In this study, the Grab Cut auto segmentation algorithm is applied first to segment garment images and extract the image’s foreground. And then, the color coherence vector (CCV) and the dominant color method are adopted to extract the color features to conduct garment image retrieval. The experimental data show that the Grab Cut auto segmentation algorithm is capable of extracting the foreground of garment images with either simple or complex background. Meanwhile, the data also indicate that compared with the garment image retrieval by extracting color features using CCV, extracting color features by dominating color method shows both higher accuracy and recall rates.