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@article{175304,
        author = {Simran Gupta and Ajit Vekhande and Sneha rathod and Shifa Momin and Anurag Shekhar},
        title = {HAND GESTURE RECOGNISITION SYSTEM},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {11},
        pages = {2386-2391},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=175304},
        abstract = {Hand gesture recognition is an emerging technology that enables human-computer interaction (HCI) by interpreting hand movements and translating them into meaningful commands. This system plays a crucial role in various applications, including assistive technologies, virtual reality (VR), gaming, robotics, and sign language interpretation. The objective of this paper is to present a comprehensive approach to developing a robust hand gesture recognition system using image processing and machine learning techniques. The proposed system captures hand gestures using a camera-based setup and processes them using computer vision techniques. The initial step involves preprocessing the input image to enhance its quality by applying noise reduction and contrast adjustments. Background subtraction and segmentation methods are then used to extract the hand region, eliminating unnecessary elements from the scene. To improve accuracy, edge detection techniques such as Canny edge detection or contour-based methods are implemented to define the hand shape precisely. Feature extraction plays a crucial role in the recognition process, as it helps differentiate between various gestures},
        keywords = {},
        month = {April},
        }