Lung cancer is a serious illness which control is mainly based on presumptive diagnosis. Besides of clinical suspicion, the diagnosis of lung cancer must be done through specific smears of sputum specimens. However, the analysis of sputum is time consuming and requires highly trained personnel to avoid high errors. Image processing techniques provide a good tool for improving the manual screening of sputum samples. In this paper we present a Computer Aided Diagnosis (CAD) system for early detection of lung cancer based on the analysis of sputum color images with the aim to attain a high specificity rate and reduce the time consumed to analyze such sputum samples. In order to form general diagnostic rules, we present a region detection technique and a feature extraction technique to determine the shape of the nuclei inside the sputum cells. The final results will be used for a (CAD) system for early detection of lung cancer.