Identification and classification of Prakriti of human using facial features

Abstract

<p>Changes in the lifestyle of individual, several of disease has emerged due to imbalance of doshas components. Ayurveda practitioners could identify the imbalance of dosha and relate the root cause of imbalance of doshas. Analysis of dosha varies from practitioner to practitioner and it requires well practiced practitioner to identify dosha. To overcome, the darshana method was adopted to automatically identify predominant dosha using facial features such as face, eyes, nose, and mouth and skin color. Computer vision and Image processing techniques were made attempted in Ayurveda domain, for identification of predominate prakriti, age, and gender of the subject. Eye Aspect Ratio (EAR), Nose Aspect Ratio (NAR), Mouth Aspect Ratio (MAR) and skin color was computed based on Euclidean distance to identify on-live predomaint prakriti of an individual. The values of MAR ≤ 0.5,EAR ≤ 0.1,NAR ≤ 0.8 as identified as vata , 0.5 ≥ MAR ≤ 0.6, 0.1 ≥ EAR ≤ 0.2, 0.8 ≥ NAR ≤ 1 as identified as pitta and MAR ≥ 0.6,EAR ≥ 0.2 and NAR ≥ 1 as identified as kapha dosha. With the features MAR, EAR and NAR classification of predominant prakriti was carried out with an accuracy of 87.5% with support vector classifier.</p>