Covid-19 is a new epidemic recently Early diagnosis of related diseases relies on the analysis of the patient’s clinical symptoms and kit testing To identify this disease efficiently and automatically, we proposed an effective classification system by identifying CT images of chest based on Histogram Equalization (HE), Gray-Level Co-Occurrence Matrix (GLCM) and Support Vector Machine (SVM) algorithm We collected 148 CT images of healthy people and 148 CT images of patients as our first-hand dataset, the size of which is 512*512*3 To enhance the features of the images, we center cropped the images to 400*400*3 GLCM is an efficient method to extract features focusing on the texture features and SVM can be accurately utilized to classify In our experiment, we proposed a 10-fold Cross-Validation (CV) to ensure the reliability of experimental results The results show that the average accuracy of our system is better than other common methods The performance of our proposed method is effective for Covid-19 identification © 2021, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd
Covid-19 Classification Based on Gray-Level Co-occurrence Matrix and Support Vector Machine