TY - GEN

T1 - A New Method for Hierarchical Image Segmentation from Visual Designs

AU - Myznikov, Pavel

AU - Huang, Yan

PY - 2020/3

Y1 - 2020/3

N2 - Hierarchical image segmentation recognizes and organizes image elements into a tree structure. The tree structure represents the semantic information of the image. It is one of the most fundamental computer vision problems. This paper focuses on the images that come from visual design such as graphic interfaces, posters, and presentations. Extracting hierarchical structure from such images allows quantitative analysis of visual design choices and reproducing designs from hand drawings or hard copies. We propose a more accurate method that incorporates the common design principles of visual designs. We compare our algorithm with seven existing approaches on the most popular websites screenshots ranked by Alexa. Our method outperforms the state-of-the-art methods in tree edit distance and F-score, and is comparable or better in the bottom-up distance.

AB - Hierarchical image segmentation recognizes and organizes image elements into a tree structure. The tree structure represents the semantic information of the image. It is one of the most fundamental computer vision problems. This paper focuses on the images that come from visual design such as graphic interfaces, posters, and presentations. Extracting hierarchical structure from such images allows quantitative analysis of visual design choices and reproducing designs from hand drawings or hard copies. We propose a more accurate method that incorporates the common design principles of visual designs. We compare our algorithm with seven existing approaches on the most popular websites screenshots ranked by Alexa. Our method outperforms the state-of-the-art methods in tree edit distance and F-score, and is comparable or better in the bottom-up distance.

KW - image representation

KW - image segmentation

KW - pattern recognition

UR - http://www.scopus.com/inward/record.url?scp=85085240851&partnerID=8YFLogxK

U2 - 10.1109/CISS48834.2020.1570616816

DO - 10.1109/CISS48834.2020.1570616816

M3 - Conference contribution

AN - SCOPUS:85085240851

T3 - 2020 54th Annual Conference on Information Sciences and Systems, CISS 2020

BT - 2020 54th Annual Conference on Information Sciences and Systems, CISS 2020

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 54th Annual Conference on Information Sciences and Systems, CISS 2020

Y2 - 18 March 2020 through 20 March 2020

ER -