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Image Classification Using Histograms and Time Series Analysis: A Study of Age-Related Macular Degeneration Screening in Retinal Image Data

  • Mohd Hanafi Ahmad Hijazi
  • Frans Coenen
  • Yalin Zheng
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6171)

Abstract

An approach to image mining is described that combines a histogram based representation with a time series analysis technique. More specifically a Dynamic Time Warping (DTW) approach is applied to histogram represented image sets that have been enhanced using CLAHE and noise removal. The focus of the work is the screening (classification) of retinal image sets to identify age-related macular degeneration (AMD). Results are reported from experiments conducted to compare different image enhancement techniques, combination of two different histograms for image classification, and different histogram based approaches. The experiments demonstrated that: the image enhancement techniques produce improved results, the usage of two histograms improved the classifier performance, and that the proposed DTW procedure out-performs other histogram based techniques in terms of classification accuracy.

Keywords

Image mining Medical image mining Dynamic time warping Image classification Histogram based classification 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Mohd Hanafi Ahmad Hijazi
    • 1
  • Frans Coenen
    • 1
  • Yalin Zheng
    • 2
  1. 1.Department of Computer ScienceUniversity of LiverpoolLiverpoolUK
  2. 2.Ophthalmology Research Unit, School of Clinical SciencesUniversity of LiverpoolLiverpoolUK

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