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In this paper, we propose a new simple and learning-free deep learningnetwork named MomentsNet, whose convolution layer, nonlinear processing layerand pooling layer are constructed by Moments kernels, binary hashing andblock-wise histogram, respectively. Twelve typical moments (includinggeometrical moment, Zernike moment, Tchebichef moment, etc.) are used toconstruct the MomentsNet whose recognition performance for binary image isstudied. The results reveal that MomentsNet has better recognition performancethan its corresponding moments in almost all cases and ZernikeNet achieves thebest recognition performance among MomentsNet constructed by twelve moments.ZernikeNet also shows better recognition performance on binary image databasethan that of PCANet, which is a learning-based deep learning network.

MomentsNet: a simple learning-free method for binary image recognition