Early Diabetes Discovery From Tongue Images

Abstract

Abstract Medical imaging shows the internal structures hidden in the skin and bone to diagnose the disease. Diabetes mellitus (DM) is a metabolic disorder that causes high blood sugar levels due to the inadequate secretion of insulin or the body does not respond properly to the secreted insulin. This paper proposes a non-invasive method to detect DM at an early stage based on the physiognomy extracted from tongue images. The tongue extends to identify the disease of a human body. However, unpredictable response of the human body parts such as the stomach, pancreas, liver and intestines revert in the tongue. The changes in the tongue ensure the dereliction of the internal organs of the human being. The changes are difference in the color and surface of the tongue. Processing of tongue image is done by fractional order Darwinian particle swarm optimization (FODPSO) algorithm. The system framework involves obtaining the image, alluring of the image, identifying the texture and color feature and finally classified as normal or diabetic. In this paper, the authors propose to diagnose DM at an early stage from tongue digital image. The tongue image is acquired and processed with FODPSO to extract edge and texture features. Tongue reflects and diagnoses diabetes in a person.