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Laminated paper counting algorithm based on compressive sensing and hough transform

机译:基于压缩感知和霍夫变换的层压纸计数算法

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According to the problem that conventional laminated paper counting algorithms have some unavoidable shortcomings such as high dependence on the quality of laminated paper and noise sensitivity, we propose a laminated paper counting algorithm based on compressive sensing (CS) and Hough transform (HT). In the proposed algorithm, the over-complete dictionary which is created by dispersing the Hough transform space of straight lines acts as the sparse matrix. Making use of high degree of sparse nature of the laminated paper image, we can obtain the accurate result through using CS theory. Experimental results on simulation images and laminated paper images have shown that our proposed algorithm can effectively restrain noise of the laminated paper image, and will get accurate experimental results with fewer CS measurements.
机译:针对传统的层压纸计数算法存在对不可避免的缺点,如对层压纸质量的高度依赖和噪声敏感性等问题,我们提出了一种基于压缩感知(CS)和霍夫变换(HT)的层压纸计数算法。在所提出的算法中,通过分散直线的霍夫变换空间而创建的超完备字典充当稀疏矩阵。利用层压纸图像的高度稀疏性,我们可以使用CS理论获得准确的结果。在模拟图像和层压纸图像上的实验结果表明,我们提出的算法可以有效抑制层压纸图像的噪声,并以较少的CS测量值获得准确的实验结果。

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