Computerized pragmatic assessment of Prakriti Dosha using tongue images- Pilot study
Joshi Manisha S, Umadevi V, Akshitha Raj B N
Journal Title:Indian Journal of Science and Technology
Objective: To design an intelligent system to identify Prakriti of a person based on tongue image analysis and machine learning algorithms. Method: Tongue images were captured using webcam and processing was done using Raspberry Pi development board. The algorithms were developed using OpenCV python libraries. Thirteen geometry features, two non-geometry features, and two texture attributes were extracted from each tongue image. These features were used to identify prakriti Vata, Pitta and Kapha. Performance of three classifiers namely, KNN, Neural network and Decision tree was verified for the precision in identifying class of the test image. Findings: KNN provided sensitivity of 42.85% for Vata, for Pitta and Kapha prakriti it was 55% and 45% respectively. With Neural network sensitivity was improved to 62.5% for Vata and Pitta and for Kapha Prakriti it was 60%. Decision tree exhibited better sensitivity of 83.33% for Vata, for Kapha and Pitta prakriti it was 75% and 71.42% respectively. During blind validation to identify prakriti, each physician was told to analyse images for said classes. This procedure resulted in sensitivity of 81.25% and 84.61% respectively.