A new approach for estimation of wavelets with non-separable kernel from a given image

Gupta, Anubha; Joshi, Sachindra; Prasad, S.

doi:10.1109/spcom.2004.1458348

Cited by 3 publications

(4 citation statements)

References 15 publications

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“…It is further shown in [1] that estimated wavelets with separable kernel have higher PSNR for the same bit-rate as compared with standard 9/7 wavelet. In this section we describe a technique for estimating a set of matched wavelets for a database of images.…”

Section: Estimating Globally Matched Wavelet Filtersmentioning

confidence: 89%

“…In [1] an approach is proposed for estimating matched wavelets for a given image. It is further shown in [1] that estimated wavelets with separable kernel have higher PSNR for the same bit-rate as compared with standard 9/7 wavelet.…”

Section: Estimating Globally Matched Wavelet Filtersmentioning

confidence: 99%

“…Here we propose an approach for locating text regions using the concept of matched wavelets proposed in [1].We use wavelet filters specifically adapted for the characteristics of text and backgrounds (or non-text regions of image). This is the unique aspect of our work.…”

Section: Introductionmentioning

confidence: 99%

“…This is the unique aspect of our work. We design these filters by extending the method proposed in [1]. Unlike previous approaches, since our segmentation scheme makes use of purely image based features, it can locate text independent of scripts, font, font-size, language, geometric transformation, geometric distortion and background texture.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Locating text in images using matched wavelets

Kumar

Khanna

Chaudhury

et al. 2005

Eighth International Conference on Document Analysis and Recognition (ICDAR'05)

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In this paper we have proposed a novel scheme for locating text regions in an image. The method is based on multiresolution wavelet analysis. We used matched wavelets to capture textural characteristics of image regions. A clustering based approach has been proposed for estimating globally matched wavelets (GMWs) for a given collection of images. Using these GMWs, we generate feature vectors for segmentation and identification of text regions in an image. Our method, unlike most of the other methods, does not require any a priori information about the font, fontsize, scripts, geometric transformation, distortion or background texture. We have tested our method on various categories of images like license plates, posters, hand written documents and document images etc. The results show proposed method to be a robust, versatile and effective tool for text extraction from images.

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Section: Estimating Globally Matched Wavelet Filtersmentioning

confidence: 89%

Section: Estimating Globally Matched Wavelet Filtersmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Locating text in images using matched wavelets

Kumar

Khanna

Chaudhury

et al. 2005

Eighth International Conference on Document Analysis and Recognition (ICDAR'05)

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Enhancement of Old Manuscript Images

Gupta

Kumar

Gupta

et al. 2007

Ninth International Conference on Document Analysis and Recognition (ICDAR 2007) Vol 2

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Text Extraction and Document Image Segmentation Using Matched Wavelets and MRF Model

Kumar

Gupta²,

Khanna

et al. 2007

IEEE Trans. on Image Process.

123

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In this paper, we have proposed a novel scheme for the extraction of textual areas of an image using globally matched wavelet filters. A clustering-based technique has been devised for estim ating globally matched wavelet filters using a collection of groundtruth images. We have extended our text extraction scheme for the segmentation of document images into text, background, and picture components (which include graphics and continuous tone images). Multiple, two-class Fisher classifiers have been used for this purpose. We also exploit contextual information by using a Markov random field formulation-based pixel labeling scheme for refinement of the segmentation results. Experimental results have established effectiveness of our approach.

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A new approach for estimation of wavelets with non-separable kernel from a given image

Cited by 3 publications

References 15 publications

Locating text in images using matched wavelets

Locating text in images using matched wavelets

Enhancement of Old Manuscript Images

Text Extraction and Document Image Segmentation Using Matched Wavelets and MRF Model

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