The Coronavirus “disease”2019 outbreak, began when unidentified pneumonia was discovered in Wuhan, China, and spread worldwide in a matter of days. A long-term negative effect on public health is caused by this outbreak, moreover, So many people lost their lives as a result of it. our study aims to “develop an intelligent computer-aided system that can detect positiveCOVID-19 cases automatically, Which may be useful with daily medical problems”. In this paper we suggested a system based on image processing and “can automatically expose discriminative features on chest X-ray images“by followed step that begin with segmentation the lung region then extracted Geometric Moment Invariants (GMI) as feature extractor, decision tree was classified the states. Our result referred to, the Hunt's Algorithm classifier achieved an accuracy of (98.7%), a sensitivity of (0.97, a specificity of (0.98), and an F-score of (0.97). The high detection performance achieved in this study explain the utility of fouse features and a appropriate classifier method for detecting “COVID-19 cases in CXR images”. With the current resources, this would be greatly helpful in speeding up disease detect.

COVID -19, Decision Tree Algorithm, Corona virus