Local radon descriptors for image search

Morteza Babaie, H. R. Tizhoosh, Amin Khatami, M. E. Shiri

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Radon transform and its inverse operation are important techniques in medical imaging tasks. Recently, there has been renewed interest in Radon transform for applications such as content-based medical image retrieval. However, all studies so far have used Radon transform as a global or quasi-global image descriptor by extracting projections of the whole image or large sub-images. This paper attempts to show that the dense sampling to generate the histogram of local Radon projections has a much higher discrimination capability than the global one. In this paper, we introduce Local Radon Descriptor (LRD) and apply it to the IRMA dataset, which contains 14,410 x-ray images as well as to the INRIA Holidays dataset with 1,990 images. Our results show significant improvement in retrieval performance by using LRD versus its global version. We also demonstrate that LRD can deliver results comparable to well-established descriptors like LBP and HOG.

Original languageEnglish (US)
Title of host publicationProceedings of the 7th International Conference on Image Processing Theory, Tools and Applications, IPTA 2017
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1-5
Number of pages5
ISBN (Electronic)9781538618417
DOIs
StatePublished - Mar 8 2018
Event7th International Conference on Image Processing Theory, Tools and Applications, IPTA 2017 - Montreal, Canada
Duration: Nov 28 2017Dec 1 2017

Publication series

NameProceedings of the 7th International Conference on Image Processing Theory, Tools and Applications, IPTA 2017
Volume2018-January

Conference

Conference7th International Conference on Image Processing Theory, Tools and Applications, IPTA 2017
Country/TerritoryCanada
CityMontreal
Period11/28/1712/1/17

Keywords

  • image descriptor
  • Image retrieval
  • IRMA dataset
  • local projections
  • Radon projections

ASJC Scopus subject areas

  • Signal Processing
  • Radiology Nuclear Medicine and imaging

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