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The authors would like to thank Dr. Attila Tanács for his detailed and helpful comments and suggestions. \n Funding text 2: This work was supported by the project ?Integrated program for training new generation of scientists in the fields of computer science?, No. EFOP-3.6.3-VEKOP-16-2017-0002. The project has been supported by the European Union and co-funded by the European Social Fund. Melinda Katona was supported by the European Union and the State of Hungary, co-financed by the European Social Fund in the framework of T?MOP 4.2.4.A/2-11-1-2012-0001 ?National Excellence Program?. 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Thanks to the revolution of smartphones and telecommunication, it also becomes more and more popular in everyday life, containing embedded web addresses or other small informative texts. While barcode reading is straightforward in images having optimal parameters (fo cus, illumination, code orientation, and position), localization of code regions is still challenging in many scenarios. Every setup has its own characteristics, there fore many approaches are justifiable. Industrial applications are likely to have more fixed parameters like illumination, camera type and code size, and processing speed and accuracy are the most important requirements. In everyday use, like with smart phone cameras, a wide variety of code types, sizes, noise levels and blurring can be observed, but the processing speed is often not crucial, and the image acquisition process can be repeated in order for successful detection. In this paper, we address this problem with two novel methods for localization of 1D barcodes based on template matching and distance transformation, and a third method for QR codes. Our proposed approaches can simultaneously localize sev eral different types of codes. We compare the effectiveness of the proposed methods with several approaches from the literature using public databases and a large set of synthetic images as a benchmark. The evaluation shows that the proposed methods are efficient, having 84.3% Jaccard accuracy, superior to other approaches. One of the presented approaches is an improvement on our previous work. Our template matching based method is computationally more complex, however, it can be adapted to specific code types producing high accuracy. The other method uses distance transformation, which is fast and gives rough regions of interests that can contain valid visual code candidates.", "fundings" : [ { "otype" : "Funding", "mtid" : 1984345, "link" : "/api/funding/1984345", "label" : "(EFOP-3.6.3-VEKOP-16-2017-00002) Támogató: EFOP", "published" : false, "snippet" : true } ], "digital" : true, "printed" : true, "sourceYear" : 2019, "foreignEdition" : true, "foreignLanguage" : true, "fullPublication" : true, "conferencePublication" : false, "nationalOrigin" : true, "missingAuthor" : false, "oaType" : "GOLD", "oaCheckDate" : "2024-02-20", "oaFree" : true, "oaLink" : "https://doi.org/10.2298/CSIS181011020K", "citationCount" : 4, "citationCountUnpublished" : 0, "citationCountWoOther" : 4, "independentCitCountWoOther" : 4, "nationalOriginCitationCount" : 0, "foreignEditionCitationCount" : 3, "doiCitationCount" : 3, "wosCitationCount" : 3, "scopusCitationCount" : 4, "wosScopusCitationCount" : 4, "wosScopusCitationCountWoOther" : 4, "wosScopusIndependentCitationCount" : 4, "wosScopusIndependentCitationCountWoOther" : 4, "independentCitationCount" : 4, "selfCitationCount" : 0, "unhandledCitationCount" : 0, "citingPubCount" : 4, "independentCitingPubCount" : 4, "citingPubCountWoOther" : 4, "independentCitingPubCountWoOther" : 4, "unhandledCitingPubCount" : 0, "citedPubCount" : 7, "citedCount" : 7, "pubStats" : { "types" : [ { "type" : "Folyóiratcikk", "typeEng" : "Journal Article", "code" : 24, "count" : 2 }, { "type" : "Könyvrészlet", "typeEng" : "Chapter in Book", "code" : 25, "count" : 2 }, { "type" : "Könyv", "typeEng" : "Book", "code" : 23, "count" : 0 }, { "type" : "Egyéb konferenciaközlemény", "typeEng" : "Conference paper", "code" : 31, "count" : 0 }, { "type" : "Egyéb konferenciakötet", "typeEng" : "Conference proceedings", "code" : 32, "count" : 0 }, { "type" : "Oltalmi formák", "typeEng" : "Protection forms", "code" : 26, "count" : 0 }, { "type" : "Disszertáció", "typeEng" : "Thesis", "code" : 28, "count" : 0 }, { "type" : "Egyéb", "typeEng" : "Miscellaneous", "code" : 29, "count" : 0 }, { "type" : "Alkotás", "typeEng" : "Achievement", "code" : 22, "count" : 0 }, { "type" : "Kutatási adat", "typeEng" : "Research data", "code" : 33, "count" : 0 } ], "citationTypes" : [ { "type" : "Folyóiratcikk", "typeEng" : "Journal Article", "code" : 24, "countUnknown" : 0, "countIndependent" : 0, "countSelfCitation" : 0 }, { "type" : "Könyvrészlet", "typeEng" : "Chapter in Book", "code" : 25, "countUnknown" : 0, "countIndependent" : 0, "countSelfCitation" : 0 }, { "type" : "Könyv", "typeEng" : "Book", "code" : 23, "countUnknown" : 0, "countIndependent" : 0, "countSelfCitation" : 0 }, { "type" : "Egyéb konferenciaközlemény", "typeEng" : "Conference paper", "code" : 31, "countUnknown" : 0, "countIndependent" : 0, "countSelfCitation" : 0 }, { "type" : "Egyéb konferenciakötet", "typeEng" : "Conference proceedings", "code" : 32, "countUnknown" : 0, "countIndependent" : 0, "countSelfCitation" : 0 }, { "type" : "Oltalmi formák", "typeEng" : "Protection forms", "code" : 26, "countUnknown" : 0, "countIndependent" : 0, "countSelfCitation" : 0 }, { "type" : "Disszertáció", "typeEng" : "Thesis", "code" : 28, "countUnknown" : 0, "countIndependent" : 0, "countSelfCitation" : 0 }, { "type" : "Egyéb", "typeEng" : "Miscellaneous", "code" : 29, "countUnknown" : 0, "countIndependent" : 0, "countSelfCitation" : 0 }, { "type" : "Alkotás", "typeEng" : "Achievement", "code" : 22, "countUnknown" : 0, "countIndependent" : 0, "countSelfCitation" : 0 }, { "type" : "Kutatási adat", "typeEng" : "Research data", "code" : 33, "countUnknown" : 0, "countIndependent" : 0, "countSelfCitation" : 0 } ], "years" : [ { "year" : 2020, "publicationCount" : 0, "citationCount" : 1, "independentCitationCount" : 1, "citingPubCount" : 1, "independentCitingPubCount" : 1, "oaStats" : null, "oaStats2" : null }, { "year" : 2021, "publicationCount" : 0, "citationCount" : 0, "independentCitationCount" : 0, "citingPubCount" : 0, "independentCitingPubCount" : 0, "oaStats" : null, "oaStats2" : null }, { "year" : 2022, "publicationCount" : 0, "citationCount" : 3, "independentCitationCount" : 3, "citingPubCount" : 3, "independentCitingPubCount" : 3, "oaStats" : null, "oaStats2" : null } ] }, "ratings" : [ { "otype" : "SjrRating", "mtid" : 10772305, "link" : "/api/sjrrating/10772305", "label" : "sjr:Q3 (2020) Scopus - 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