Mouse Gesture Recognition using Back Propagation Neural Network

To Understand Mouse motions are often exhibit as a pattern recognition weakness. So as to convey pictorial messages to a receiver, a mouse expresses motion patterns referred to as gestures; these patterns area unit variable however dissimilar associated have an associated significance. The Pattern recognition by any processor or machine are often executed via varied ways like Hidden Markov Models (HMM), Linear Programming (LP) and Neural Networks (NNs). Every technique has its own advantages and disadvantages. This paper reviews why using ANNs particularly is best suited to analyzing mouse gesture patterns. All implementation work is carried out in MATLAB (Matrix Laboratory) could be a problem-oriented language and interactive surroundings for numerical computation, image, and programming. MATLAB is de facto normal for analyzing information, developing algorithms, and making models and applications. The research proposed work uses Techniques like Vector Quantization, Genetic Algorithms and Neural Networks; therefore such work is implemented using Neural Networks toolbox (NNTool).In certain scenarios, we have successfully demonstrated that Neural Networks can be used for the Gesture recognition in with more than 99.7% success rate.