Gabor filters for document analysis in indian bilingual documents

Pati, Peeta Basa; Raju, Savitri; Pati, Nibedita; Ramakrishnan, A. G.

doi:10.1109/icisip.2004.1287637

Cited by 33 publications

(21 citation statements)

References 14 publications

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“…Dhanya et al [14], has achieved better performance in the latter method rather than the Pati et al [24]. But this would fail for some English characters which are descender dominant.…”

Section: Related Workmentioning

confidence: 99%

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Scripts and Numerals Identification From Printed Multilingual Document Images

Abirami¹

2011

Computer Science Conference Proceedings

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“…Dhanya et al [14], has achieved better performance in the latter method rather than the Pati et al [24]. But this would fail for some English characters which are descender dominant.…”

Section: Related Workmentioning

confidence: 99%

“…In the work of Pati et al [24] script recognition in bilingual document script (between Tamil and English) was performed using Gabor filters. Dhanya et al [9], has performed script classification using Gabor filters for bilingual document images in frequency domain.…”

Section: Related Workmentioning

confidence: 99%

Scripts and Numerals Identification From Printed Multilingual Document Images

Abirami¹

2011

Computer Science Conference Proceedings

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“…Several studies have been conducted in the literature for page layout analysis using the multi-channel Gabor filters [43,38,44], while few ones have explored Gabor filters for ancient document image segmentation. For instance, Ribeiro et al proposed an optical character recognition system for ancient document recognition by applying fuzzy methods on aligned oriented features extracted using Gabor filters in the training step [45].…”

Section: Gabor Featuresmentioning

confidence: 99%

Use of SLIC superpixels for ancient document image enhancement and segmentation

et al. 2015

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Designing reliable and fast segmentation algorithms of ancient documents has been a topic of major interest for many libraries and the prime issue of research in the document analysis community. Thus, we propose in this article a fast ancient document enhancement and segmentation algorithm based on using Simple Linear Iterative Clustering (SLIC) superpixels and Gabor descriptors in a multi-scale approach. Firstly, in order to obtain enhanced backgrounds of noisy ancient documents, a novel foreground/background segmentation algorithm based on SLIC superpixels, is introduced. Once, the SLIC technique is carried out, the background and foreground superpixels are classified. Then, an enhanced and non-noisy background is achieved after processing the background superpixels. Subsequently, Gabor descriptors are only extracted from the selected foreground superpixels of the enhanced gray-level ancient book document images by adopting a multi-scale approach. Finally, for ancient document image segmentation, a foreground superpixel clustering task is performed by partitioning Gabor-based feature sets into compact and well-separated clusters in the feature space. The proposed algorithm does not assume any a priori information regarding document image content and structure and provides interesting results on a large corpus of ancient documents. Qualitative and numerical experiments are given to demonstrate the enhancement and segmentation quality.

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“…So, whatever the method is, our tests have shown that these methods are not robust to the variability of our corpus. That's why, we have decided like [8,9] to use texture-based approaches. Gabor filters, autocorrelation function, fractal or wavelet analysis are interesting methods because they allow a text/graphic separation without using any kind of structural information.…”

Section: Evaluation Of the Existing Methods On Ancient Booksmentioning

confidence: 99%