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Scale Space Co-Occurrence HOG Features for Word Spotting in Handwritten Document Images
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Author(s): C. Thontadari (Department of Computer Science, Kuvempu University, Shimogga, India)and C. J. Prabhakar (Department of Computer Science, Kuvempu University, Shimogga, India)
Copyright: 2016
Volume: 6
Issue: 2
Pages: 16
Source title:
International Journal of Computer Vision and Image Processing (IJCVIP)
DOI: 10.4018/IJCVIP.2016070105
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Abstract
In this paper, the authors proposed a Scale Space Co-occurrence Histograms of Oriented Gradients method (SS Co-HOG) for retrieving words from digitized handwritten documents. The poor performance of HOG based word spotting in handwritten documents is due to that HOG ignores spatial information of neighboring pixels whereas Co-HOG captures the spatial information of neighboring pixels through counting the occurrence of the gradient orientations of two or more neighboring pixels. The authors employed three scale parameter representation of an image and at each scale, they divide the word image into blocks and Co-HOG features are extracted from each block and finally concatenate them into form a feature descriptor. The proposed method is evaluated using precision and recall metrics through experimentation conducted on popular datasets such as IAM and GW and confirmed that their method outperforms for both the datasets.
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