Multiple Line Skew Estimation of Handwritten Images of Documents Based on a Visual Perception Approach
Identifieur interne : 000461 ( Main/Exploration ); précédent : 000460; suivant : 000462Multiple Line Skew Estimation of Handwritten Images of Documents Based on a Visual Perception Approach
Auteurs : B. Mello [Brésil] ; Ángel Sánchez [Espagne] ; C. Cavalcanti [Brésil]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2011.
Abstract
Abstract: This paper introduces Viskew: a new algorithm to estimate the skew of text lines in digitized documents. The algorithm is based on a visual perception approach where transition maps and morphological operators simulate human visual perception of documents. The algorithm was tested in a set of 19,500 synthetic text line images and 400 images of documents with multiple skew angles. The skew angles for the synthetic dataset are known and our algorithm achieved the lowest mean square error in average when compared with two other algorithms.
Url:
DOI: 10.1007/978-3-642-23678-5_15
Affiliations:
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<front><div type="abstract" xml:lang="en">Abstract: This paper introduces Viskew: a new algorithm to estimate the skew of text lines in digitized documents. The algorithm is based on a visual perception approach where transition maps and morphological operators simulate human visual perception of documents. The algorithm was tested in a set of 19,500 synthetic text line images and 400 images of documents with multiple skew angles. The skew angles for the synthetic dataset are known and our algorithm achieved the lowest mean square error in average when compared with two other algorithms.</div>
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