Efficient Text Detection in Color Images by Eliminating Reflectance Component
Identifieur interne : 000E61 ( Main/Exploration ); précédent : 000E60; suivant : 000E62Efficient Text Detection in Color Images by Eliminating Reflectance Component
Auteurs : Miyoung Choi [Corée du Sud] ; Hyungil Choi [Corée du Sud]Source :
- Lecture Notes in Computer Science [ 0302-9743 ] ; 2007.
Abstract
Abstract: This paper proposes a new approach to eliminate the reflectance component for the detection of text in color images. Color images, printed by color printing technology, normally have an illumination component as well as a reflectance component. It is well known that a reflectance component usually obstructs the task of detecting and recognizing objects like texts in the scene, since it blurs out an overall image. We have developed an approach that efficiently removes reflectance components while preserving illumination components. We decided whether an input image hits Normal or Polarized for determining the light environment, using the histogram which consisted of a red component. We were able to go ahead through the ability to extract by reducing the blur phenomenon of text by light because reflection component by an illumination change and removed it and extracted text. The experimental results have shown a superior performance even when an image has a complex background. Text detection and recognition performance is influenced by changing the illumination condition. Our method is robust to the images with different illumination conditions.
Url:
DOI: 10.1007/978-3-540-74484-9_103
Affiliations:
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<front><div type="abstract" xml:lang="en">Abstract: This paper proposes a new approach to eliminate the reflectance component for the detection of text in color images. Color images, printed by color printing technology, normally have an illumination component as well as a reflectance component. It is well known that a reflectance component usually obstructs the task of detecting and recognizing objects like texts in the scene, since it blurs out an overall image. We have developed an approach that efficiently removes reflectance components while preserving illumination components. We decided whether an input image hits Normal or Polarized for determining the light environment, using the histogram which consisted of a red component. We were able to go ahead through the ability to extract by reducing the blur phenomenon of text by light because reflection component by an illumination change and removed it and extracted text. The experimental results have shown a superior performance even when an image has a complex background. Text detection and recognition performance is influenced by changing the illumination condition. Our method is robust to the images with different illumination conditions.</div>
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