Indian Journal of Science and Technology
Year: 2020, Volume: 13, Issue: 48, Pages: 4679-4698
Joshi Manisha S1*, Umadevi V1, Akshitha Raj B N1
1B M S College of Engineering, Bangalore, India. Tel.: 9739433108
Email: [email protected]
Received Date:28 October 2020, Accepted Date:04 December 2020, Published Date:30 December 2020
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.
Keywords: Prakriti dosha; tongue image analysis; machine learning
© 2020 Joshi Manisha S et al.This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Published By Indian Society for Education and Environment (iSee)
Subscribe now for latest articles and news.