DocumentCode
2476511
Title
Automated stroke ending analysis for drawing tool classification
Author
Vill, Maria C. ; Sablatnig, Robert
Author_Institution
Pattern Recognition & Image Process. Group, Vienna Univ. of Technol., Vienna, Austria
fYear
2008
fDate
8-11 Dec. 2008
Firstpage
1
Lastpage
4
Abstract
This paper proposes a drawing tool recognition method based on features calculated from the shape of stroke endings. The application for this method is to help art historians to identify the drawing tool used for a drawing. Since the style of a drawing depends on the drawing tool used, drawing tool recognition is an important step toward a style analysis. A dominant feature of a drawn stroke is its ending. Several features regarding curvature, proportions etc. are calculated out of the shape of the endings. These features are then used to classify stroke endings with a SVM classifier.
Keywords
art; image classification; image segmentation; image texture; object recognition; support vector machines; SVM classifier; automated stroke ending analysis; drawing tool classification; drawing tool recognition; historian art; image classification; image segmentation; stroke texture analysis; Art; Gray-scale; Image analysis; Image segmentation; Joining processes; Painting; Pattern analysis; Pattern recognition; Shape; Skeleton;
fLanguage
English
Publisher
ieee
Conference_Titel
Pattern Recognition, 2008. ICPR 2008. 19th International Conference on
Conference_Location
Tampa, FL
ISSN
1051-4651
Print_ISBN
978-1-4244-2174-9
Electronic_ISBN
1051-4651
Type
conf
DOI
10.1109/ICPR.2008.4761171
Filename
4761171
Link To Document