SHS Web of Conf.
Volume 166, 20232022 International Conference on Education Innovation and Modern Management (EIMM 2022)
|Number of page(s)||8|
|Published online||05 May 2023|
Pattern segmentation based on PoolNet and boundary connectivity
Beijing Institute of Fashion Technology, Beijing, 100029, China
* Corresponding author: firstname.lastname@example.org
Traditional image segmentation algorithms need to design features manually. Therefore, based on the advantage of PoolNet in object detection, this paper proposes a clothing pattern segmentation algorithm combining PoolNet detection and boundary connectivity. This algorithm has more fine edges than traditional segmentation. Especially in the case of similar background before and after, we can get more complete pattern elements, and have better results in segmentation accuracy.
Key words: Significance test / Boundary connectivity / Pattern segmentation / PoolNet
© The Authors, published by EDP Sciences, 2023
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.