RETRACTED ARTICLE: A novel semi supervised learning algorithm for thyroid and ulcer classification in tongue image

Tongue diagnosis is used to identify various diseases in the body now a day. The tongue image indicates the condition of different parts in body and signs in the tongue shows the misbehavior of internal parts of the body. This paper proposes a semi-supervised learning based approach to identify ulcer and thyroid of a patient by analyzing tongue image. The midpoint of tongue indicates intestine organ; if there is any problem in the intestine, it will be reflected in the midpoint of the tongue. Initially preprocessing steps are implemented to reduce noise and other irrelevant pixels from the image. Then segmentation is done to extract the specific part from the tongue and parameters collected from a healthy patient are considered to be the threshold value. The parameters collected from the extracted tongue image are compared with the threshold value, and the current condition of a patient is identified. A semi-supervised technique is introduced with a show the subtle elements of the patient whether he is in a protected or essential condition. The simulation work does with the MATLAB simulation environment utilizing adaptive semi-supervised learning technique. The simulation output shows the productivity of the semi-supervised learning strategy and its ability to recognize the issues of the tongues. Subsequently the proposed demonstrate delivers better highlights human body tissues. More than 97% efficiency accomplished by utilizing semi adaptive supervised learning technique.