2002
DOI: 10.1109/tcsvt.2002.806812
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Document image segmentation using wavelet scale-space features

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Cited by 60 publications
(25 citation statements)
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References 28 publications
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“…In the current study, features are extracted by the 2W decomposed upto third level, dyadic wavelet packet (2WP) decomposed upto third level, the MW as implemented in [3] and the proposed MWP. Daubechies 6 filter has been used for the feature extraction using the 2W and 2WP decomposition.…”
Section: Resultsmentioning
confidence: 99%
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“…In the current study, features are extracted by the 2W decomposed upto third level, dyadic wavelet packet (2WP) decomposed upto third level, the MW as implemented in [3] and the proposed MWP. Daubechies 6 filter has been used for the feature extraction using the 2W and 2WP decomposition.…”
Section: Resultsmentioning
confidence: 99%
“…After the selection of significant bases, a local estimator, which constitutes a nonlinear operator followed by a smoothing filter, is applied to each subbands [3]. It gives high energy value for the regions in each subbands where frequency components are strong, otherwise low energy value is obtained where it is weak.…”
Section: Local Energy Estimation and Smoothingmentioning
confidence: 99%
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“…The segmentation and extraction of text regions from a document image is a difficult problem which has received significant attention in the literature [12], [13], [14], [15], [16]. This stage of processing, however, is beyond the scope of this paper, and manual extraction of text regions is performed for all experiments.…”
Section: Preprocessing Of Imagesmentioning
confidence: 99%
“…A novel method for segmenting text and graphics part of document images based on textural cues is presented in [1]. The segmentation method uses the notion of discrete sc wavelet analysis and statistical pattern recognition.…”
Section: Introductionmentioning
confidence: 99%