Comparison of Similarity Measurement Metrics on Medical Image Data
Aswini Kumar Samantaray, Amol D. Rahulkar · 2019
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.