A memristor-based RBM circuit implementation and application in license plate image processing

Abstract

License plate image processing is crucial in the field of intelligent transportation and public safety. Because of the influence of the shooting environment, imaging equipment, and other factors, the quality of the obtained license plate image is usually low, which affects the accuracy of license plate recognition. Image super-resolution reconstruction and image denoising technology not only improve image quality but also help further analysis and processing of the image. In this work, a memristive circuit of the restricted Boltzmann machine (RBM) is designed and applied in license plate image processing. The memristive circuit design mainly contains three modules: a generation module of hidden units, a reconstruction module of visible units, and a regeneration module of hidden units. The training process is transferred from software to on-chip implementation by the memristive circuit implementation. After applying license plate image super-resolution and image denoising, the effectiveness and superiority of the proposed memristive RBM circuit are verified by simulation and comparison results.