International Journal of Image, Graphics and Signal Processing (IJIGSP)
IJIGSP Vol. 9, No. 8, 8 Aug. 2017
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Signature based Document Image Retrieval Using Multi-level DWT Features
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Author(s)
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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