A computer vision-based shape-classification system using image projection and a neural network

In this research, a computer vision-based shape-recognition system which combines an image projection and the back propagation neural network is proposed. The system uses the image projection and features of the projection histogram to represent the shape, and uses the back propagation neural network to classify the shape. In this research, a fast normalisation scheme is developed which is especially designed for the image projection. II can find the same projection axis no matter how the object is oriented. Therefore, the proposed system can be invariant to scale, translation, and orientation variations. This research finds that the direct representation scheme of the back propagation neural net has better accuracy that? the binary coding representation scheme. This research also finds that classification accuracy of the proposed system is greater than 98.8% and its processing speed is also very fast. Therefore, the proposed system is feasible for use in shape classification.