Effective multiresolution arc segmentation : algorithms and performance evaluation

Arc segmentation plays an important role in the process of graphics recognition from scanned images. The GREC arc segmentation contest shows there is a lot of room for improvement in this area. This paper proposes a multiresolution arc segmentation method based on our previous seeded circular tracki...

Ausführliche Beschreibung

Bibliographische Detailangaben
Veröffentlicht in:IEEE transactions on pattern analysis and machine intelligence. - 1979. - 26(2004), 11 vom: 15. Nov., Seite 1491-506
1. Verfasser: Song, Jiqiang (VerfasserIn)
Weitere Verfasser: Lyu, Michael R, Cai, Shijie
Format: Aufsatz
Sprache:English
Veröffentlicht: 2004
Zugriff auf das übergeordnete Werk:IEEE transactions on pattern analysis and machine intelligence
Schlagworte:Comparative Study Evaluation Study Journal Article Research Support, Non-U.S. Gov't Validation Study
Beschreibung
Zusammenfassung:Arc segmentation plays an important role in the process of graphics recognition from scanned images. The GREC arc segmentation contest shows there is a lot of room for improvement in this area. This paper proposes a multiresolution arc segmentation method based on our previous seeded circular tracking algorithm which largely depends on the OOPSV model. The newly-introduced multiresolution paradigm can handle arcs/circles with large radii well. We describe new approaches for arc seed detection, arc localization, and arc verification, making the proposed method self-contained and more efficient. Moreover, this paper also brings major improvement to the dynamic adjustment algorithm of circular tracking to make it more robust. A systematic performance evaluation of the proposed method has been conducted using the third-party evaluation tool and test images obtained from the GREC arc segmentation contests. The overall performance over various arc angles, arc lengths, line thickness, noises, arc-arc intersections, and arc-line intersections has been measured. The experimental results and time complexity analyses on real scanned images are also reported and compared with other approaches. The evaluation result demonstrates the stable performance and the significant improvement on processing large arcs/circles of the MAS method
Beschreibung:Date Completed 02.12.2004
Date Revised 10.12.2019
published: Print
Citation Status MEDLINE
ISSN:1939-3539