article

Consensus-based clustering for document image segmentation

Authors:

Soumyadeep Dey,

Jayanta Mukherjee,

Shamik SuralAuthors Info & Claims

International Journal on Document Analysis and Recognition, Volume 19, Issue 4

Pages 351 - 368

https://doi.org/10.1007/s10032-016-0275-1

Published: 01 December 2016 Publication History

Abstract

Segmentation of a document image plays an important role in automatic document processing. In this paper, we propose a consensus-based clustering approach for document image segmentation. In this method, the foreground regions of a document image are grouped into a set of primitive blocks, and a set of features is extracted from them. Similarities among the blocks are computed on each feature using a hypothesis test-based similarity measure. Based on the consensus of these similarities, clustering is performed on the primitive blocks. This clustering approach is used iteratively with a classifier to label each primitive block. Experimental results show the effectiveness of the proposed method. It is further shown in the experimental results that the dependency of classification performance on the training data is significantly reduced.

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Cited By

Stewart SBarrett B(2017)Document Image Page Segmentation and Character Recognition as Semantic SegmentationProceedings of the 4th International Workshop on Historical Document Imaging and Processing10.1145/3151509.3151518(101-106)Online publication date: 10-Nov-2017
https://dl.acm.org/doi/10.1145/3151509.3151518

Consensus-based clustering for document image segmentation
1. Computing methodologies
  1. Artificial intelligence
    1. Computer vision
      1. Computer vision problems
  2. Machine learning
    1. Learning paradigms
      1. Supervised learning
      2. Unsupervised learning

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cover image International Journal on Document Analysis and Recognition

International Journal on Document Analysis and Recognition Volume 19, Issue 4

December 2016

88 pages

ISSN:1433-2833

EISSN:1433-2825

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Copyright © Copyright © 2016 Springer-Verlag Berlin Heidelberg.

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Springer-Verlag

Berlin, Heidelberg

Publication History

Published: 01 December 2016

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Cited By

Stewart SBarrett B(2017)Document Image Page Segmentation and Character Recognition as Semantic SegmentationProceedings of the 4th International Workshop on Historical Document Imaging and Processing10.1145/3151509.3151518(101-106)Online publication date: 10-Nov-2017
https://dl.acm.org/doi/10.1145/3151509.3151518

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