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Estimation-decoding on LDPC-based 2D-barcodes

机译:基于LDPC的2D-BarCodes对解码解码

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摘要

In this paper we propose an extension of the Estimation-Decoding algorithm for the decoding of our Data Matrix Code (DMC), which is based on Low-Density-Parity-Check (LDPC) codes and is designed for use in industrial environment. To include possible damages in the channel-model, a Markov-modulated Gaussian channel (MMGC) was chosen to represent everything in between the embossing of a LDPC-based DMC and the camera-based acquisition. The MMGC is based on a Hidden-Markov-Model (HMM) that turns into a two-dimensional model when used in the context of DMCs. The proposed ED2D-algorithm (Estimation-Decoding in two dimensions) is implemented to operate on a 2D-LDPC-Markov factor graph that comprises of a LDPC code's Tanner-graph and a 2D-HMM. For a subsequent comparison between different barcodes in industrial environment, a simulation of typical damages has been implemented. Tests showed a superior decoding behavior of our LDPC-based DMC decoded with the ED2D-decoder over the standard Reed-Solomon-based DMC.
机译:在本文中,我们提出了用于解码我们的数据矩阵代码(DMC)的估计解码算法的扩展,其基于低密度 - 奇偶校验(LDPC)代码,并且设计用于工业环境。为了包括频道模型中可能的损坏,选择了Markov调制的高斯信道(MMGC)来表示基于LDPC的DMC的压花和基于相机的采集之间的所有内容。 MMGC基于隐藏的Markov-Model(HMM),该模型(HMM)在DMC的上下文中使用时转换为二维模型。所提出的ED2D算法(两个维度中的估计解码)被实现为在2D-LDPC-Markov因子图上操作,该图包括LDPC代码的Tanner-Graph和2D-HMM。对于工业环境中不同条形码之间的随后比较,已经实施了典型损坏的模拟。测试显示了基于LDPC的DMC的卓越的解码行为,并在标准簧片基于所罗门的DMC上用ED2D解码器解码。

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