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An Abstract Image Representation Based on Edge Pixel Neighborhood Information (EPNI)

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EurAsia-ICT 2002: Information and Communication Technology (EurAsia-ICT 2002)

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Abstract

In this paper we introduce a new abstract image representation based on Edge Pixel Neighborhood Information (EPNI). It is applied in image retrieval problem when user query is a fast drawn, rough example. The representation consists of two main elements. A neighborhood vector f and a vicinity table v. The former contains the frequencies of edge pixels with similar directions and the latter holds information about neighboring edge directions. An image similarity measure based on EPNI components is also designed and compared with some other measures known from the literature. Experimental results show a good recognition accuracy in a data set containing a wide range of color images.

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Author information

Authors and Affiliations

  1. School of Electrical, Computer and Telecommunications Engineering, University of Wollongong, Wollongong, NSW, 2522, Australia

    Abdolah Chalechale & Alfred Mertins

Authors
  1. Abdolah Chalechale
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  2. Alfred Mertins
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Editor information

Editors and Affiliations

  1. Faculty of Mathematics and Computer Science Computer Science Department, Shahid Bahonar University, 22 Bahman Bulvard, Kerman, Iran

    Hassan Shafazand

  2. Fraunhofer IPSI, Dolivostr. 15, 64293, Darmstadt, Germany

    Hassan Shafazand

  3. Institute of Software Technology, Vienna University of Technology, Favoritenstr. 9/188, 1040, Vienna, Austria

    A. Min Tjoa

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© 2002 Springer-Verlag Berlin Heidelberg

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Chalechale, A., Mertins, A. (2002). An Abstract Image Representation Based on Edge Pixel Neighborhood Information (EPNI). In: Shafazand, H., Tjoa, A.M. (eds) EurAsia-ICT 2002: Information and Communication Technology. EurAsia-ICT 2002. Lecture Notes in Computer Science, vol 2510. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-36087-5_8

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  • DOI: https://doi.org/10.1007/3-540-36087-5_8

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-00028-0

  • Online ISBN: 978-3-540-36087-2

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