Model-Based Chart Image Recognition
Identifieur interne : 001560 ( Main/Merge ); précédent : 001559; suivant : 001561Model-Based Chart Image Recognition
Auteurs : Weihua Huang [Singapour] ; Lim Tan [Singapour] ; Kheng Leow [Singapour]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2004.
Abstract
Abstract: In this paper, we introduce a system that aims at recognizing chart images using a model-based approach. First of all, basic chart models are designed for four different chart types based on their characteristics. In a chart model, basic object features and constraints between objects are defined. During the chart recognition, there are two levels of matching: feature level matching to locate basic objects and object level matching to fit in an existing chart model. After the type of a chart is determined, the next step is to do data interpretation and recover the electronic form of the chart image by examining the object attributes. Experiments were done using a set of testing images downloaded from the internet or scanned from books and papers. The results of type determination and the accuracies of the recovered data are reported.
Url:
DOI: 10.1007/978-3-540-25977-0_8
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