Indian Sign Language Recognition Using Scale-Invariant Feature Transform by Depth Sensor
Jayesh Gangrade, Shweta Gangrade, Ashish Mishra, Gautam Kumar, Vinit Kumar Gunjan · 2023
Deaf and hard of hearing people in the Indian community now have a way to communicate with society because to Indian Sign Language (ISL). The hand is accorded significant importance in the framework of the ISL. ISL is composed of both static and dynamic sign hand gestures. Both static and dynamic signs are made up of three components: hand movement, hand orientation, and hand position. The proposed method can recognize static ISL signs. The technique that was suggested makes use of the Microsoft Kinect sensor to locate and separate a hand from its background in a complex scene. SIFT, which stands for “scale-invariant feature transform,” was used to extract the feature. The SIFT algorithm is invariant under changes in perspective, orientation, and lighting. Recognize the 10 ISL digit movements with an accuracy of 94.9% using a multi support vector machine (MSVM).