the recognition of Hand gestures has become a critical point as it is widely used in everyday applications. the challenge in this is to improve the recognition effect and develop a fast recognition method. Glove and led-based methods involve external devices in detecting and interpreting hand gestures, making human-computer interaction less natural. So, different approaches have been used previously that use purely hand gestures in many systems based on human-computer interaction. This system provides a more natural human-computer interaction; it must be made efficient processing speed of classifying the test data (images) from among the training data (database stored for gestures recognition). This speed makes gesture recognition more effective and reliable to use as compared to previously proposed methods. In this research paper, a proposed system based on a camera-based interactive wall display using bare hand gestures with efficient processing speed for controlling the speed of the mouse and other functions. This system has three modules: one uses Genetic Algorithm and Otsu thresholding to identify the query images as the right or wrong gesture and perform the correct action in case of the proper motion, another module controls functions outside of PowerPoint files or Word documents, e.g., to open folders and go through drives, and the third module uses the convexity hull method for finding the number of fingers open in the user's gesture and operates accordingly.