Evolutionary projection selection for Radon barcodes

H. R. Tizhoosh, S. Rahnamayan

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


Recently, Radon transformation has been used to generate barcodes for tagging medical images. The under-sampled image is projected in certain directions, and each projection is binarized using a local threshold. The concatenation of the thresholded projections creates a barcode that can be used for tagging or annotating medical images. A small number of equidistant projections, e.g., 4 or 8, is generally used to generate short barcodes. However, due to the diverse nature of digital images, and since we are only working with a small number of projections (to keep the barcode short), taking equidistant projections may not be the best course of action. In this paper, we proposed to find n optimal projections, whereas n< 180, in order to increase the expressiveness of Radon barcodes. We show examples for the exhaustive search for the simple case when we attempt to find 4 best projections out of 16 equidistant projections and compare it with the evolutionary approach in order to establish the benefit of the latter when operating on a small population size as in the case of micro-DE. We randomly selected 10 different classes from IRMA dataset (14,400 x-ray images in 58 classes) and further randomly selected 5 images per class for our tests.

Original languageEnglish (US)
Title of host publication2016 IEEE Congress on Evolutionary Computation, CEC 2016
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages8
ISBN (Electronic)9781509006229
StatePublished - Nov 14 2016
Event2016 IEEE Congress on Evolutionary Computation, CEC 2016 - Vancouver, Canada
Duration: Jul 24 2016Jul 29 2016

Publication series

Name2016 IEEE Congress on Evolutionary Computation, CEC 2016


Conference2016 IEEE Congress on Evolutionary Computation, CEC 2016

ASJC Scopus subject areas

  • Artificial Intelligence
  • Modeling and Simulation
  • Computer Science Applications
  • Control and Optimization


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