• Madhuri Pethe
• Atul Surwase
• Vikas Marathe

Diabetes mellitus (DM) and its complications leading to diabetic retinopathy (DR) are soon to become one of the 21st century’s major health problems. The main drawback is that there is lack of awareness of the people on eating habits. It is characterized by hyperglycemia. The persistent hyperglycemia of diabetes leads to damage malfunction and failure of different organs such as kidneys, eyes, nerves, blood vessels and heart. To combat this approaching epidemic, this paper proposes a noninvasive method to detect DM. Three groups of features extracted from tongue images. They include color, texture, and geometry [1]. A noninvasive capture device with image correction first captures the tongue images. A tongue color gamut is established with 12 colors representing the tongue color features. The texture values of eight blocks strategically located on the tongue surface, with the additional mean of all eight blocks are used to characterize the nine tongue texture features. Finally, 13 features extracted from tongue images based on measurements, distances, areas, and their ratios represent the geometry features. Applying a combination of the 34 features, the proposed method can separate Healthy/DM tongues.

Diabetes mellitus (DM) detection, tongue color features, tongue geometry features, tongue texture features,SVM,ANN.

"Detection of Diabetes mellitus using Tongue Color, Texture, And Shape Features", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.667-672, June 2019, Available :http://www.jetir.org/papers/JETIR1907F90.pdf

"Detection of Diabetes mellitus using Tongue Color, Texture, And Shape Features", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp667-672, June 2019, Available at : http://www.jetir.org/papers/JETIR1907F90.pdf