Signature based Document Image Retrieval Using Multi-level DWT Features

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Author(s)

Umesh D. Dixit 1,* M. S. Shirdhonkar 2

1. Department of Electronics & Communication Engineering, B.L.D.E.A’s, V. P. Dr. P. G. Halakatti C.E.T, Bijapur, India

2. Department of Computer Science & Engineering, B.L.D.E.A’s, V. P. Dr. P. G. Halakatti C.E.T, Bijapur, India

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2017.08.05

Received: 21 Feb. 2016 / Revised: 26 May 2016 / Accepted: 8 May 2017 / Published: 8 Aug. 2017

Index Terms

Document image, Signature extraction, Signature based retrieval, Multi-level DWT, Distance measures, Connected components

Abstract

Automatic signature extraction from document image and retrieval has a large number of applications such as in business offices, organizations, institutes and digital libraries. Hence it has attracted a lot of researchers from the field of document image analysis and processing. This paper proposes a method for automatic signature extraction and signature based document image retrieval using multi-level discrete wavelet transform features. Since the distance measures play a vital role in pattern analysis, classification and clustering, in this paper we also compared the results of retrieval using 7 distance metrics such as Euclidean, Canberra, City-block, Chebychev, Cosine, Hamming and Jaccard. Results obtained in this paper shows that city-block distance with multi-level DWT features outperforms the other 6 distance metrics used for comparison.

Cite This Paper

Umesh D. Dixit, M. S. Shirdhonkar,"Signature based Document Image Retrieval Using Multi-level DWT Features", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.9, No.8, pp.42-49, 2017. DOI: 10.5815/ijigsp.2017.08.05

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