1) The document presents a proposed approach for detecting lung cancer from CT images using image processing and machine learning techniques. It involves preprocessing images, extracting features using grey level co-occurrence matrix (GLCM) and classifying images using support vector machine (SVM). 2) A key step is applying GLCM to extract texture features from lung regions, capturing relationships between pixel pairs. Features like energy, entropy, homogeneity and contrast are calculated from the GLCM matrix. 3) The proposed system aims to automate lung cancer detection from CT images to reduce errors and make the process more accurate and efficient compared to manual detection. This could help detect cancer at earlier stages when treatment outcomes are better.