A compounded encoding and decoding algorithm for product tracing based on the information‐grayscale matrix
This paper proposes a compounded encoding and decoding algorithm based on the information‐grayscale matrix. Generally, it is very difficult to track the original information in the circulation of commodity. This algorithm is aimed to be applied to product tracing, especially fast‐moving consumer goo...
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| Vydáno v: | International journal of numerical modelling Ročník 32; číslo 3 |
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| Médium: | Journal Article |
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Bognor Regis
Wiley Subscription Services, Inc
01.05.2019
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| ISSN: | 0894-3370, 1099-1204 |
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| Abstract | This paper proposes a compounded encoding and decoding algorithm based on the information‐grayscale matrix. Generally, it is very difficult to track the original information in the circulation of commodity. This algorithm is aimed to be applied to product tracing, especially fast‐moving consumer goods (FMCG). According to the traceability requirements of product information, we construct the structure of basic information code with information bits and check bits. The encoded information can be mapped into an information matrix through visible and invisible processes after extending the matrix, and we generate the corresponding grayscale matrix by calculating the relationship between the four‐dimensional matrices of each matrix cell. It is the information‐grayscale matrix that forms our product traceability information matrix. When the matrix is damaged in logistics transportation, we can get very high matrix information recovery rate through the decoding algorithm of the information‐grayscale matrix including self‐recovery, cross recovery, mutual recovery, and iteration; finally, the 2 × DA + DC structure can obtain 85% recovery rate when the damage rate reaches 70% for 10 million data volumes, and it can be extended into various structures. In addition, the algorithm can achieve a good balance between encoding rate and recovery rate and can be extended into different structures. |
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| AbstractList | This paper proposes a compounded encoding and decoding algorithm based on the information‐grayscale matrix. Generally, it is very difficult to track the original information in the circulation of commodity. This algorithm is aimed to be applied to product tracing, especially fast‐moving consumer goods (FMCG). According to the traceability requirements of product information, we construct the structure of basic information code with information bits and check bits. The encoded information can be mapped into an information matrix through visible and invisible processes after extending the matrix, and we generate the corresponding grayscale matrix by calculating the relationship between the four‐dimensional matrices of each matrix cell. It is the information‐grayscale matrix that forms our product traceability information matrix. When the matrix is damaged in logistics transportation, we can get very high matrix information recovery rate through the decoding algorithm of the information‐grayscale matrix including self‐recovery, cross recovery, mutual recovery, and iteration; finally, the 2 × DA + DC structure can obtain 85% recovery rate when the damage rate reaches 70% for 10 million data volumes, and it can be extended into various structures. In addition, the algorithm can achieve a good balance between encoding rate and recovery rate and can be extended into different structures. This paper proposes a compounded encoding and decoding algorithm based on the information‐grayscale matrix. Generally, it is very difficult to track the original information in the circulation of commodity. This algorithm is aimed to be applied to product tracing, especially fast‐moving consumer goods (FMCG). According to the traceability requirements of product information, we construct the structure of basic information code with information bits and check bits. The encoded information can be mapped into an information matrix through visible and invisible processes after extending the matrix, and we generate the corresponding grayscale matrix by calculating the relationship between the four‐dimensional matrices of each matrix cell. It is the information‐grayscale matrix that forms our product traceability information matrix. When the matrix is damaged in logistics transportation, we can get very high matrix information recovery rate through the decoding algorithm of the information‐grayscale matrix including self‐recovery, cross recovery, mutual recovery, and iteration; finally, the 2 × DA + DC structure can obtain 85% recovery rate when the damage rate reaches 70% for 10 million data volumes, and it can be extended into various structures. In addition, the algorithm can achieve a good balance between encoding rate and recovery rate and can be extended into different structures. |
| Author | Liu, Wen Jing Wan, Guo Chun Xia, Zi Wei Tong, Mei Song |
| Author_xml | – sequence: 1 givenname: Guo Chun surname: Wan fullname: Wan, Guo Chun organization: Tongji University – sequence: 2 givenname: Wen Jing surname: Liu fullname: Liu, Wen Jing organization: Tongji University – sequence: 3 givenname: Zi Wei surname: Xia fullname: Xia, Zi Wei organization: Tongji University – sequence: 4 givenname: Mei Song surname: Tong fullname: Tong, Mei Song email: mstong@tongji.edu.cn organization: Tongji University |
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| References | 2008 1950; 29 2017 2011; 34 1993 2015 2016; 29 2011 1962; 8 2010; 93‐A 1996; 42 1948; 27 China Coding Center (e_1_2_8_3_1) 2008 e_1_2_8_14_1 e_1_2_8_2_1 e_1_2_8_5_1 e_1_2_8_4_1 e_1_2_8_7_1 e_1_2_8_6_1 e_1_2_8_9_1 e_1_2_8_8_1 e_1_2_8_10_1 e_1_2_8_11_1 e_1_2_8_12_1 Gao C (e_1_2_8_13_1) 2017 |
| References_xml | – year: 2011 – volume: 93‐A start-page: 1912 issue: 11 year: 2010 end-page: 1917 article-title: A note on the branch‐and‐cut approach to decoding linear block codes publication-title: IEICE Trans Fundam Electron, Commun Comput Sci – volume: 42 start-page: 1687 issue: 7 year: 1996 end-page: 1697 article-title: Trellis decoding complexity of linear block codes publication-title: IEEE Trans Inf Theory – start-page: 36 year: 2008 end-page: 89 article-title: Application guide for barcode technology in logistics publication-title: China Meas Press – volume: 29 start-page: 147 issue: 2 year: 1950 end-page: 160 article-title: Error detecting and correcting codes publication-title: Bell Syst Tech J – volume: 27 start-page: 379 issue: 4 year: 1948 end-page: 423 article-title: A mathematical theory of communication publication-title: Bell Syst Tech J – year: 1993 – volume: 8 start-page: 21 issue: 1 year: 1962 end-page: 28 article-title: Low‐density parity‐check codes publication-title: IRE Trans Inf Theory – volume: 34 start-page: 797 issue: 2 year: 2011 end-page: 798 article-title: RFID technology, systems, and applications publication-title: J Netw Comput Appl – year: 2015 – start-page: 1118 year: 2017 end-page: 1121 article-title: An efficient image feature extraction approach based on discrete information coding matrix algorithm publication-title: Prog Electromagn Res Symp Fall – volume: 29 start-page: 1106 issue: 6 year: 2016 end-page: 1117 article-title: An efficient encoding and decoding algorithm for tracking circulation of commodity by discretizing information matrix publication-title: Int J Numer Modell Electron Networks Devices Fields – ident: e_1_2_8_10_1 – ident: e_1_2_8_9_1 doi: 10.1109/TIT.1962.1057683 – ident: e_1_2_8_11_1 – ident: e_1_2_8_14_1 doi: 10.1109/18.556665 – ident: e_1_2_8_12_1 doi: 10.1002/jnm.2169 – ident: e_1_2_8_4_1 doi: 10.1007/978-1-4419-5906-5 – start-page: 36 year: 2008 ident: e_1_2_8_3_1 article-title: Application guide for barcode technology in logistics publication-title: China Meas Press – ident: e_1_2_8_8_1 doi: 10.1587/transfun.E93.A.1912 – ident: e_1_2_8_5_1 doi: 10.1002/j.1538-7305.1948.tb01338.x – ident: e_1_2_8_7_1 – start-page: 1118 year: 2017 ident: e_1_2_8_13_1 article-title: An efficient image feature extraction approach based on discrete information coding matrix algorithm publication-title: Prog Electromagn Res Symp Fall – ident: e_1_2_8_2_1 doi: 10.1016/j.jnca.2010.07.008 – ident: e_1_2_8_6_1 doi: 10.1002/j.1538-7305.1950.tb00463.x |
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| SubjectTerms | Algorithms Codes Coding Consumer goods Data recovery Decoding encoding and decoding information‐grayscale matrix Logistics Product information product tracing Structural damage |
| Title | A compounded encoding and decoding algorithm for product tracing based on the information‐grayscale matrix |
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