An Interface for Communication for the Deaf Using Hand Gesture Recognition through Computer Vision and Natural Language Processing

Abstract

Hand gesture recognition is essential for conquering various challenges and improving human existence. A machine’s capacity to interpret human behaviors and their significance is being used in a large range of applications. Sign language recognition is one area of particular attention. This study will provide a deep analysis of use cases and technologies utilized now for current gesture recognition of hand, recognition of sign language, research done on it and the previous history of the same. The approaches under investigation are logically broken down into the following stages: data gathering, pre-processing of hand data, segmentation of data and features, feature extraction of the refined data, and picture recognition. At each level, several algorithms are explained, and their merits are assessed. We also draw attention to the drawbacks and restrictions of the study of gesture recognition. We also talk about a project on hand gesture recognition using computer vision and natural language processing, which will help the deaf community communicate with people using the idea of artificial sign language to a translator of natural language.