Pneumonia disease is a dangerous one declared by WHO. It may be affected in one or both lungs generally affected by viruses or bacteria. Since the arrival of the novel Covid-19, several types of research have been initiated for its accurate prediction across the world. The earlier lung disease pneumonia is closely related to Covid-19, as several patients died due to high chest congestion (pneumonic condition). It is challenging to differentiate between Covid-19 and pneumonia lung diseases for medical experts. Chest X-ray imaging is the most reliable method for lung disease prediction. In this paper, we propose a novel framework for lung disease predictions differentiated by two categories “Pneumonia” and “Normal” from the chest X-ray images of patients using covnets, data acquisition, image quality enhancement, features extraction, and disease anticipation. Numerical illustrations were also provided to prove the results and discussions.

Image Processing, Chest X-ray image, CNN, Data acquisition, and Covnets