Meher, Kunal2025-05-202025-05-2020241660-6795https://atlasuniversitylibraryir.in/handle/123456789/767uGDXThis paper reviews hand gesture recognition techniques by leveraging the strengths of OpenCV and TensorFlow, two of the most widely used libraries in computer vision and deep learning. OpenCV's sophisticated image processing capabilities are utilized for preprocessing, feature extraction, and establishing a solid foundation for further analysis. TensorFlow is employed to construct and train deep neural networks capable of identifying fine-grained details and subtle variations in hand gestures. This integration allows for precise and accurate differentiation and understanding of a predefined set of gestures, demonstrating the potential for robust hand gesture recognition systems.envHand Gesture RecognitionOpenCVTensorFlowComputer VisionDeep LearningImage ProcessingNeural NetworksArticle