A novel approach for text detection in images using structural features
Identifieur interne : 000215 ( France/Analysis ); précédent : 000214; suivant : 000216A novel approach for text detection in images using structural features
Auteurs : H. Trai [France, Viêt Nam] ; A. Lux [France] ; H. L. Nguyen T [Viêt Nam] ; A. Boucher [France]Source :
- Lecture notes in computer science [ 0302-9743 ] ; 2005.
Descripteurs français
- Pascal (Inist)
English descriptors
- KwdEn :
Abstract
We propose a novel approach for finding text in images by using ridges at several scales. A text string is modelled by a ridge at a coarse scale representing its center line and numerous short ridges at a smaller scale representing the skeletons of characters. Skeleton ridges have to satisfy geometrical and spatial constraints such as the perpendicularity or non-parallelism to the central ridge. In this way, we obtain a hierarchical description of text strings, which can provide direct input to an OCR or a text analysis system. The proposed method does not depend on a particular alphabet, it works with a wide variety in size of characters and does not depend on orientation of text string. The experimental results show a good detection.
Affiliations:
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Pascal:05-0391618Le document en format XML
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<front><div type="abstract" xml:lang="en">We propose a novel approach for finding text in images by using ridges at several scales. A text string is modelled by a ridge at a coarse scale representing its center line and numerous short ridges at a smaller scale representing the skeletons of characters. Skeleton ridges have to satisfy geometrical and spatial constraints such as the perpendicularity or non-parallelism to the central ridge. In this way, we obtain a hierarchical description of text strings, which can provide direct input to an OCR or a text analysis system. The proposed method does not depend on a particular alphabet, it works with a wide variety in size of characters and does not depend on orientation of text string. The experimental results show a good detection.</div>
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