Automatic identification techniques of tuberculosis bacteria

Tuberculosis is a serious illness which control is based on early diagnosis. A technique commonly used consist of analyzing sputum images for detecting bacilli. However, the analysis of sputum is quite expensive, time consuming and requires highly trained personnel to avoid high errors. Image processing techniques provide a good tool for improving the manual screening of samples. In this paper we present a new bacilli detection technique with the aim to attain a high specificity rate and therefore for reducing the time required to analyze such sputum samples. This technique is based on the heuristic acknowledge extracted from the bacilli shape contour. It uses also the color information for image segmentation and finally a classification tree is used to categorize if a sample is positive or negative.