Yoga's various acknowledged physical and mental advantages have contributed significantly to the popularity of the practise. Due to a lack of datasets and the requirement to detect mudra in real time, recognising yoga hand mudras is a difficult undertaking. The yoga hand mudras are used as input in the proposed work, and the two features Scale Invariant Feature Transform (SIFT) and Speeded-Up Robust Features (SURF) are retrieved, followed by machine learning techniques namely Gaussian Naive Bayes (GNB) are used for classification. In the experimental results the performance of SIFT with GNB yields better results.