Indonesian Journal of Electrical Engineering and Informatics (IJEEI)
Vol 6, No 4: December 2018

A Novel Approach for Feature Selection and Classifier Optimization Compressed Medical Retrieval Using Hybrid Cuckoo Search

Vamsidhar, Enireddy (KL University)
Saichandana, B. (Shri Vishnu Engineering College for Women)
Harikiran, J. (Shri Vishnu Engineering College for Women)



Article Info

Publish Date
25 Dec 2018

Abstract

Nowadays, huge data bases are required to store the Digital medical images so that they can be accessed easily on requirement. To retrieve the diagnostic images, radiologist and physicians are using Content based image retrieval (CBIR). Algorithms extract features like texture, edge, color and shape from an image in CBIR systems and these extracted features from the input and are compared for similarity with the features of images in database. In this paper, Lossless compression is used for storage and effective transmission in inadequate bandwidth. Visually lossless image compression is obtained using the Daubechies wavelet with Huffman coding. Gabor transforms are utilized to extract the shape and texture features from the images. Features are selected with Mutual Information (MI) and the proposed wrapper based Cuckoo Search (CS) technique. Extracted features are fed as input to the proposed partial Recurrent Neural Networks (RNN) for the classification. The network is optimized hybrid Particle Swarm Optimization and Cuckoo Search. It was observed that the classification accuracy acquired is satisfactory

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Journal Info

Abbrev

IJEEI

Publisher

Subject

Computer Science & IT Electrical & Electronics Engineering

Description

Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is a peer reviewed International Journal in English published four issues per year (March, June, September and December). The aim of Indonesian Journal of Electrical Engineering and Informatics (IJEEI) is to publish high-quality ...