Classification of Chest X-Ray Images using Wavelet and MFCC Features and Support Vector Machine Classifier

Author:

Owida H. A.,Al-Ghraibah A.,Altayeb M.

Abstract

The shortage and availability limitation of RT-PCR test kits and is a major concern regarding the COVID-19 pandemic. The authorities' intention is to establish steps to control the propagation of the pandemic. However, COVID-19 is radiologically diagnosable using x-ray lung images. Deep learning methods have achieved cutting-edge performance in medical diagnosis software assistance. In this work, a new diagnostic method for detecting COVID-19 disease is implemented using advanced deep learning. Effective features were extracted using wavelet analysis and Mel Frequency Cepstral Coefficients (MFCC) method, and they used in the classification process using the Support Vector Machine (SVM) classifier. A total of 2400 X-ray images, 1200 of them classified as Normal (healthy) and 1200 as COVID-19, have been derived from a combination of public data sets to verify the validity of the proposed model. The experimental results obtained an overall accuracy of 98.8% by using five wavelet features, where the classification using MFCC features, MFCC-delta, and MFCC-delta-delta features reached accuracy around 97% on average. The results show that the proposed model has reached the required level of success to be applicable in COVID 19 diagnosis.

Publisher

Engineering, Technology & Applied Science Research

Cited by 11 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. hFedLAP: A Hybrid Federated Learning to Enhance Peer-to-Peer;Engineering, Technology & Applied Science Research;2024-06-01

2. X-COVNet: Externally Validated Model for Computer-Aided Diagnosis of Pneumonia-Like Lung Diseases in Chest X-Rays Based on Deep Transfer Learning;2024-05-21

3. MFCC in audio signal processing for voice disorder: a review;Multimedia Tools and Applications;2024-04-27

4. Development of Personalized Health Detection Device for Covid-19;2024 2nd International Conference on Intelligent Data Communication Technologies and Internet of Things (IDCIoT);2024-01-04

5. An automated system to distinguish between Corona and Viral Pneumonia chest diseases based on image processing techniques;Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization;2023-09-30

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