PSO-BP algorithm implementation for material surface image identification

Implementation of neural network for acoustic computation is not ne w. In this paper, a new improved method in predicting material surface from photographic image was implemented using a hybrid of particle swarm optimization and back-propagation neural network (PSO-BP) algorithm. Before the system clas sified the data using PSO-BP algorithm, the photographic images of room surfaces need to be extracted using Gray Level Co-occurrence Matrix (GLCM) and Modified Zernike Moments. The result indicated that the PSO-BP algorithm have a hig her accuracy compared to the BP algorithm, managed to record highest accuracy of 88% as opposed to 81.3% for the latter.

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