z-logo
open-access-imgOpen Access
A Data Mining Approach for Compressed Medical Image Retrieval
Author(s) -
Vamsidhar Enireddy,
R. Kiran Kumar
Publication year - 2012
Publication title -
international journal of computer applications
Language(s) - English
Resource type - Journals
ISSN - 0975-8887
DOI - 10.5120/8199-1591
Subject(s) - computer science , information retrieval , image (mathematics) , data mining , data science , artificial intelligence
The digital medical images are stored in large databases for easy accessibility and Content based image retrieval (CBIR) is used to retrieve diagnostic cases similar to the query medical image. Image compression condense the amount of data required to represent an image, it reduces the storage and transmission requirements. The medical image retrieval problem for compressed images is studied in this paper. The proposed method integrates image retrieval to retrieve diagnostic cases similar to the query medical image and image compression techniques to minimize the bandwidth utilization. Haar wavelet is used for image compression without losses. Edge and texture features are extracted from the medical compressed medical images using Sobel edge detector and Gabor transforms respectively. The classification accuracy of retrieval is evaluated using Naive Bayes and Support Vector Machine. General Terms Image retrieval, Image Compression, Data Mining, Algorithm.

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom