Preprocessing and presorting of envelope images for automatic sorting using OCR
Pattern Recognition
Page segmentation using the description of the background
Computer Vision and Image Understanding - Special issue on document image understanding and retrieval
Probabilistic latent semantic indexing
Proceedings of the 22nd annual international ACM SIGIR conference on Research and development in information retrieval
Unsupervised learning by probabilistic latent semantic analysis
Machine Learning
IEEE Transactions on Pattern Analysis and Machine Intelligence
Recognizing Mathematical Expressions Using Tree Transformation
IEEE Transactions on Pattern Analysis and Machine Intelligence
Music, Gestalt, and Computing - Studies in Cognitive and Systematic Musicology
Music, Gestalt, and Computing - Studies in Cognitive and Systematic Musicology
Document Image Segmentation as Selection of Voronoi Edges
DIA '97 Proceedings of the 1997 Workshop on Document Image Analysis
Methodology for Flexible and Efficient Analysis of the Performance of Page Segmentation Algorithms
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
A Full English Sentence Database for Off-Line Handwriting Recognition
ICDAR '99 Proceedings of the Fifth International Conference on Document Analysis and Recognition
Extraction, layout analysis and classification of diagrams in PDF documents
ICDAR '03 Proceedings of the Seventh International Conference on Document Analysis and Recognition - Volume 2
An online composite graphics recognition approach based on matching of spatial relation graphs
International Journal on Document Analysis and Recognition
mSpace mobile: a UI gestalt to support on-the-go info-interaction
CHI '06 Extended Abstracts on Human Factors in Computing Systems
Gabor Filter Based Text Extraction from Digital Document Images
IIH-MSP '06 Proceedings of the 2006 International Conference on Intelligent Information Hiding and Multimedia
Document zone content classification and its performance evaluation
Pattern Recognition
An interactive example-driven approach to graphics recognition in engineering drawings
International Journal on Document Analysis and Recognition
Text line segmentation of historical documents: a survey
International Journal on Document Analysis and Recognition
Feature Extraction for Document Image Segmentation by pLSA Model
DAS '08 Proceedings of the 2008 The Eighth IAPR International Workshop on Document Analysis Systems
GOAL: towards understanding of graphic objects from architectural to line drawings
GREC'09 Proceedings of the 8th international conference on Graphics recognition: achievements, challenges, and evolution
TIPS: on finding a tight isothetic polygonal shape covering a 2d object
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
Negotiating gestalt: artistic expression by coalition formation between agents
SG'05 Proceedings of the 5th international conference on Smart Graphics
Image classification by a two-dimensional hidden Markov model
IEEE Transactions on Signal Processing
Document image segmentation using wavelet scale-space features
IEEE Transactions on Circuits and Systems for Video Technology
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This paper introduces how Gestalt properties can be used for identifying various components in a document image. That the human mind makes a holistic approach to vision rather than a disintegrated approach is shown to be useful for document analysis. Since the major constituent components textual or non-textual in a document page are arranged in a rectilinear fashion, rectilinear/isothetic decomposition of different components are made on a document page. After representing the page as a feature set of its polygonal covers corresponding to the distinct regions of interest, each polygon is iteratively decomposed into the sub-polygons tightly enclosing the corresponding sub-components to capture the overall information as well as the necessary details to the desired level of precision. Subsequently, these components and sub-components are analyzed using Gestalt laws/properties, which have been explained in detail in the context of this work. Text regions, tabular structures, and various graphic objects readily admit some of the Gestalt properties. We have tested our algorithm on several benchmark datasets, and some relevant results have been produced here to demonstrate the effectiveness and elegance of the proposed method.