抽象的な

Robust Technique for Detection and Classification of Glands from Human Tissue Samples

Prachi Kawalkar, Girish Talmale

Demand for augmented hardiness, higher responsible and high automation of image analysis algorithms is apparent in recent years. Precise designation and prognosis is crucial to scale back the high death rate. In this paper, we are going to discuses different techniques for pre-processing, segmentation, feature extraction and classification of biomedical images to detect and classify glands in human tissues. Additionally here we concentrate on some issues and problems regarding to biomedical images and solution to that particular problems. The crisis is such as noisy images, different straining techniques and calculation of pixel values. The study covers different methods like polar conversion, along with object based segmentation and SVM classification. As a result final outcome shows the structure of glands along with the grading results.