Proceedings ArticleDOI
A CRF Based Scheme for Overlapping Multi-colored Text Graphics Separation
Ritu Garg,Ehtesham Hassan,Santanu Chaudhury,M. Gopal +3 more
- pp 1215-1219
TLDR
A novel framework for segmentation of documents with complex layouts performed by combination of clustering and conditional random fields (CRF) based modeling and has been extensively tested on multi-colored document images with text overlapping graphics/image.Abstract:
In this paper, we propose a novel framework for segmentation of documents with complex layouts. The document segmentation is performed by combination of clustering and conditional random fields (CRF) based modeling. The bottom-up approach for segmentation assigns each pixel to a cluster plane based on color intensity. A CRF based discriminative model is learned to extract the local neighborhood information in different cluster/color planes. The final category assignment is done by a top-level CRF based on the semantic correlation learned across clusters. The proposed framework has been extensively tested on multi-colored document images with text overlapping graphics/image.read more
Citations
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A comprehensive survey of mostly textual document segmentation algorithms since 2008
TL;DR: This survey highlights the variety of the approaches that have been proposed for document image segmentation since 2008 and provides a clear typology of documents and of document images segmentation algorithms.
Proceedings ArticleDOI
Research on the Text Detection and Extraction from Complex Images
TL;DR: This paper tries to find a new way which can utilize existing methods to detect and extract text from born-digital image.
Book ChapterDOI
Extraction of Doodles and Drawings from Manuscripts
TL;DR: An approach to separate the non-texts from texts of a manuscript, mainly in the form of doodles and drawings of some exceptional thinkers and writers, and a computational approach to recover the struck-out texts to reduce human effort.
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Consensus-based clustering for document image segmentation
TL;DR: A consensus-based clustering approach for document image segmentation that is used iteratively with a classifier to label each primitive block and shows that the dependency of classification performance on the training data is significantly reduced.
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An intelligent character recognition method to filter spam images on cloud
TL;DR: STRHOG, an extended version of HOG that is helpful for filtering spam images on cloud and a fair comparison with other methods, nearest neighbor classifier is used for the intelligent character recognition.
References
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Proceedings Article
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Proceedings Article
Large Margin DAGs for Multiclass Classification
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Proceedings ArticleDOI
A Visual Vocabulary for Flower Classification
M.-E. Nilsback,Andrew Zisserman +1 more
TL;DR: It is demonstrated that by developing a visual vocabulary that explicitly represents the various aspects that distinguish one flower from another, it can overcome the ambiguities that exist between flower categories.
Journal ArticleDOI
Comparison of texture features based on Gabor filters
TL;DR: The grating cell operator is the only one that selectively responds only to texture and does not give false response to nontexture features such as object contours and the texture detection capabilities of the operators are compared.