Generating Ground Truthed Dataset of Chart Images: Automatic or Semi-automatic?
Identifieur interne : 000C35 ( Main/Exploration ); précédent : 000C34; suivant : 000C36Generating Ground Truthed Dataset of Chart Images: Automatic or Semi-automatic?
Auteurs : Weihua Huang [Singapour] ; Lim Tan [Singapour] ; Jiuzhou Zhao [Singapour]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2008.
Abstract
Abstract: Ground truthing tools mainly fall into two categories: automatic and semi-automatic. In this paper, we first discuss the pros and cons of the two approaches. We then report our own work on designing and implementing systems for generating a chart image dataset and multi-level ground truth data. Both semi-automatic and automatic approaches were adopted, resulting in two independent systems. The dataset as well as the ground truth data are publicly available so that other researchers can access them for evaluating and comparing performances of different systems.
Url:
DOI: 10.1007/978-3-540-88188-9_25
Affiliations:
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<front><div type="abstract" xml:lang="en">Abstract: Ground truthing tools mainly fall into two categories: automatic and semi-automatic. In this paper, we first discuss the pros and cons of the two approaches. We then report our own work on designing and implementing systems for generating a chart image dataset and multi-level ground truth data. Both semi-automatic and automatic approaches were adopted, resulting in two independent systems. The dataset as well as the ground truth data are publicly available so that other researchers can access them for evaluating and comparing performances of different systems.</div>
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