Content-based Medical Image Retrieval in using Wavelet Based GLCM and ANN

  • T.Venketbabu, Dr.R.Arunkumar, Dr.M.Balasubramanian


An experimental comparison of several different image descriptors is presented in order to restore the content-based images. Many of the documents describing new techniques and descriptions for content-based image retrieval describe the most appropriate of the proposed new methods without providing a complete comparison with all previously proposed methods.. The main determination of this document is to deliver an effective tool that is used for efficient recovery of medical images from a large content of the medical imaging database and used for additional medical diagnostic purposes. In this proposed system, we introduced wavelet techniques and GLCM based feature extraction technique. To improve the Image Retrieval in Medical Applications we have used Feature level fusion and ACO feature selection technique. To evaluate the proposed performance LISS dataset is used. For image retrieval classification in this proposed system has analysed with three different classification techniques are used such as ANN, Random forest and KNN. From the result analysis shows that the ANN based technique provides better performance in terms of 97% of accuracy.

Keyword: Image Retrieval, Medical Applications, LISS dataset, Wavelet Techniques and ANN.

How to Cite
T.Venketbabu, Dr.R.Arunkumar, Dr.M.Balasubramanian. (2020). Content-based Medical Image Retrieval in using Wavelet Based GLCM and ANN. International Journal of Advanced Science and Technology, 29(05), 10228 - 10239. Retrieved from