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Comparison of Similarity Measurement Metrics on Medical Image Data

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

Abstract

Similarity measurement plays an important role to solve many pattern recognition problems such as classification, clustering and particularly the content based image retrieval problems. In this paper, a detailed comparison of 10 similarity measures has been presented for medical image retrieval. Different types of medical images from databases such as NEMA, OASIS and EXACT09 are used to evaluate the performance. Features of all the medical images are extracted using Log-Gabor wavelet. The effectiveness of all the distance metrics are investigated and tested on more than 800 medical images from the databases. It is observed from the experimental results that the retrieval performance can be improved by the distance measures like Bray- Curtis and Canberra distance metric as compared to other existing distance based approach.

Original languageEnglish
Title of host publication2019 10th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538659069
DOIs
Publication statusPublished - 07-2019
Event10th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2019 - Kanpur, India
Duration: 06-07-201908-07-2019

Publication series

Name2019 10th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2019

Conference

Conference10th International Conference on Computing, Communication and Networking Technologies, ICCCNT 2019
Country/TerritoryIndia
CityKanpur
Period06-07-1908-07-19

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Hardware and Architecture
  • Software
  • Electrical and Electronic Engineering

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