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Text extraction and enhancement of binary images using cellular automata

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Abstract

Text characters embedded in images represent a rich source of information for content-based indexing and retrieval applications. However, these text characters are difficult to be detected and recognized due to their various sizes, grayscale values, and complex backgrounds. Existing methods cannot handle well those texts with different contrast or embedded in a complex image background. In this paper, a set of sequential algorithms for text extraction and enhancement of image using cellular automata are proposed. The image enhancement includes gray level, contrast manipulation, edge detection, and filtering. First, it applies edge detection and uses a threshold to filter out for low-contrast text and simplify complex background of high-contrast text from binary image. The proposed algorithm is simple and easy to use and requires only a sample texture binary image as an input. It generates textures with perceived quality, better than those proposed by earlier published techniques. The performance of our method is demonstrated by presenting experimental results for a set of text based binary images. The quality of thresholding is assessed using the precision and recall analysis of the resultant text in the binary image.

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Authors and Affiliations

  1. Department of Information Technology, Birla Institute of Technology, Mesra, Ranchi, India

    G. Sahoo

  2. Department of Information Technology, Lingaya’s University, Faridabad, Haryana, India

    Tapas Kumar & B. L. Raina

  3. Department of Electrical Engineering, Indian Institute of Technology, Delhi, India

    C. M. Bhatia

Authors
  1. G. Sahoo
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  2. Tapas Kumar
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  3. B. L. Raina
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  4. C. M. Bhatia
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Corresponding author

Correspondence to Tapas Kumar.

Additional information

G. Sahoo received his P. G. degree from Utkal University, India, in 1980 and Ph.D. degree in the area of computational mathematics from Indian Institute of Technology, Kharagpur in 1987. He is currently a professor and heading the Department of Computer Science and Engineering in Birla Institute of Technology, India.

His research interests include theoretical computer science, parallel and distributed computing, image processing, and pattern recognition.

Tapas Kumar graduated from Amravati University, India in 1998. He received the master degree in computer science from Guru Jambeshwar University of Secience and Technology, India, and Ph.D. degree in the area of cellular automata application in image processing from Birla Institute of Technology Mesra, India. He is currently working as a lecturer (selection grade) at Lingaya’s Institute of Management and Technology (LIMAT), Fardiabad, India.

His research interests include image processing, especially the application of cellular automata as a computing tool.

B. L. Raina received his P. G. degree from Jammu and Kashmir University in 1962 and Ph.D. degree in the area of computational mathematics from Indian Institute of Technology, New Delhi, India in 1973. He is currently working as a professor in the Department of Information Technology at Lingaya’s Institute of Management and Technology (LIMAT), Fardabad, India.

His research interests include applied numerical techniques, graph theory, image processing, and cryptography.

C. M. Bhatia received his B.Eng. (Hons) degree in electrical engineering from Jabalpur University, India in 1965. He received the P. G. degree from Indian Institute of Technology (IIT) Roorkee, in applied electronics and servomechanism in 1968, and the Ph.D. from IIT Delhi in 1973. He is currently a professor and dean (P.G. studies) at Lingaya’s University, India.

His research interests include power electronics and variable speed drives, flexible AC transmission system (FACTS), microprocessor and microcomputer based system digital filters, and image processing.

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Sahoo, G., Kumar, T., Raina, B.L. et al. Text extraction and enhancement of binary images using cellular automata. Int. J. Autom. Comput. 6, 254–260 (2009). https://doi.org/10.1007/s11633-009-0254-9

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  • DOI: https://doi.org/10.1007/s11633-009-0254-9

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