Quality Improvement for Analysis of Leukemia Images through Contrast Stretch Methods

Computer image processing develops very fast and plays an important role in wide applications of engineering and sciences. Leukemia is a malignant disease (Cancer) seen in people of any age groups either in children or adults aged over 50 years. In most of the cases microscopic images usually inadequate to identify the type of the cell. The traditional morphology test done by a hematologist to look under the microscope is a time consuming and tedious job. Diagnosis through this approach requires very costly equipment and may not be installed in all hospitals and clinics. Further the noises and blurriness effect during image acquisition often leads to false diagnosis of leukemia. An automatic image enhancement and segmentation system can make the inspection procedure of leukocytes much easier and faster and the amount of data that can be analyzed by such a clinician handle more data than they normally can handle. In this paper four contrast stretch based enhancement methods are implemented for analysis of leucocytes. A comparative analysis is done on local contrast stretching, global contrast stretching, dark contrast stretching, bright contrast stretching methods. All these methods involve threshold mapping which often useful to attain segmented results.