Automated Recognition of Yoga Mudras through Image Processing

Yoga, an ancient practice, uses specific hand gestures called mudras, to reduce stress, enhance focus, and improve mental health. However, existing systems for Yoga Mudra Recognition have been limited in scope, recognizing only a small number of mudras and often lacking accuracy under diverse and challenging conditions. To address these shortcomings, this study introduces a novel approach that overcomes these limitations by employing advanced image processing techniques. By leveraging cutting-edge computer vision algorithms, the system is capable of accurately identifying 22 different yoga mudras, marking a significant expansion from previous models. The methodology involves capturing detailed hand landmarks, applying sophisticated preprocessing steps, extracting critical features such as finger positions, and utilizing SVM for precise classification. The refined dataset, combined with extensive experiments considering various hand shapes, lighting conditions, and backgrounds, resulted in an impressive accuracy of 99.87%. This gesture recognition technology enhances mindfulness and holistic wellness across various environments.