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On foreground — background separation in low quality document images

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International Journal of Document Analysis and Recognition (IJDAR) Aims and scope Submit manuscript

Abstract

This paper deals with effective separation of foreground and background in low quality document images suffering from various types of degradations including scanning noise, aging effects, uneven background, or foreground, etc. The proposed algorithm shows an excellent adaptability to tackle with these problems of uneven illumination and local changes or nonuniformity in background and foreground colors. The approach is primarily designed for (not restricted to) processing of color documents but it works well in the gray scale domain too. Test document set considers samples (in color as well as in gray scale) of old historical documents including manuscripts of high importance. The data set used in this study consists of hundred images. These images are selected from different sources including image databases that had been scanned from working notebooks of famous writers who used to write with quill or pencil generating very low contrast between foreground and background. Evaluation of foreground extraction method has been judged by computing the accuracy of extracting handwritten lines and words from the test images. This evaluation shows that the proposed method can extract lines and words with accuracies of about 84% and 93%, respectively. Apart from this quantitative method, a qualitative evaluation is also presented to compare the proposed method with one popular technique for foreground/background separation in document images.

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Authors and Affiliations

  1. Computer Vision & Pattern Recognition Unit, Indian Statistical Institute, 203, B. T. Road, 700108, Kolkata, INDIA

    Utpal Garain

  2. Laboratoire PSI - FRE CNRS 2645, UFR des Sciences, University of Rouen, 76821, Mont Saint Aignan cedex, FRANCE

    Thierry Paquet & Laurent Heutte

Authors
  1. Utpal Garain
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  2. Thierry Paquet
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  3. Laurent Heutte
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Correspondence to Utpal Garain.

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Utpal Garain received both of his B.E. and M.E. in Computer Science and Engineering from Jadavpur University, Kolkata in 1994 and 1997, respectively and PhD from Indian Statistical Institute, Kolkata in 2005. Mr. Garain started his career as a software professional in industry and later on joined as a research personnel at the Indian Statistical Institute, where he is currently a full-time faculty member. He is one of the key scientists involved in the development of a bilingual (Devanagri & Bangla) OCR system, the first of its kind in India. Mr. Garain's areas of interest are in digital document processing including optical character recognition for Indian language scripts, online character recognition, document data compression, artificial immune system, etc.

Thierry Paquet Thierry PAQUET received the Ph.D. degree from the University de Rouen in 1992 in the field of Pattern Recognition. From 1992 to 2002 he has been appointed as a Senior Lecturer at the University of Rouen where he taught Signal and Image Processing. From 1992 to 1996 he was involved in an industrial collaboration with Matra MCS and the French Postal Research Center (SRTP) for the automatisation of mail sorting and bank checks reading. During this period he also worked on stochastic models and Information Criteria. Thierry PAQUET was appointed as a full professor in 2002 at the University of Rouen. His current research area concern Handwritten Document processing including Biometry, Writer adaptation of recognition systems, handwritten document categorization for industrial purposes, complex layout analysis for historical document analysis. Thierry PAQUET is the president of the French association for research in written communication (GRCE).

Laurent Heutte Laurent Heutte (30/05/1964) received his Ph.D. degree in Computer Engineering from the University of Rouen, France, in 1994. From 1996 to 2004, he was a Senior Lecturer in Computer Engineering and Automatic Control at the University of Rouen. Since 2004, he has been a Professor in the same university. Professor Heutte's present research interests are multiple classifier systems, off-line cursive handwriting analysis and recognition, handwritten document layout analysis and information extraction from handwritten documents. Since 2003, he is an Associate Editor of Pattern Recognition journal and the representative member of the French association of pattern recognition (AFRIF) in the Governing Board of the IAPR.

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Garain, U., Paquet, T. & Heutte, L. On foreground — background separation in low quality document images. IJDAR 8, 47–63 (2006). https://doi.org/10.1007/s10032-005-0007-4

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  • DOI: https://doi.org/10.1007/s10032-005-0007-4

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