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Optisk sopsortering med spiralkoder
Halmstad University, School of Information Technology.
Halmstad University, School of Information Technology.
2019 (Swedish)Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
Abstract [en]

This thesis is a study of possible applications for a technology based on “spiral codes” applied in the field of waste sorting. The report shows the development and reading of spiral codes through image analysis, and studies for the results of the technique in practical tests. Today, food waste is separated from other household waste using an optical technique that distinguishes the garbage bags with respect to color. The concept is called “Gr¨ona p˚asen”(Green bag) as the bags for food waste are colored green. We examine the posibilty to identify the contents and origin of the bag by printing different spiral codes on garbage bags and using image analysis, to identify the contents and origin of the bag. The result from lab environment shows a correct identification of garbage bags of 100 % with 6 identities. For each analyzed garbage bag, on average 29.56 printed spiral codes were found on the garbage bag with a correct identification of each spiral code of 92.04 %. Which results in a correct identification of the garbage bags at 99.9 % with only three found spiral codes.

Abstract [sv]

Detta examensarbete är en undersökning av möjliga tillämpningar för en teknik baserad på “spiralkoder” applicerat på området sopsortering. Rapporten visar framtagning och avläsning av spiralkoder genom bildanalys, och undersökningar för resultatet av tekniken i praktiska test. Idag avskiljs matavfall från övriga hushållssopor med hjälp av en optisk teknik som särskiljer soppåsarna med avseende på färg. Konceptet benämns “Gröna påsen” då påsarna för matavfall är av grön färg. Vi undersöker om det genom att trycka olika spiralkoder på soppåsar går att, med hjälp av bildanalys, identifiera påsens innehåll och ursprung. Resultatet från labbmiljö visar en korrekt identifiering av soppåsar på 100 % med 6 st identiteter. För varje analyserad soppåse hittades i snitt 29.56 st tryckta spiralkoder på soppåsen med en korrekt identifiering av varje spiralkod på 92.04 %. Vilket resulterar i en korrekt identifiering av soppåsarna på 99.9 % vid endast tre funna spiralkoder.

Place, publisher, year, edition, pages
2019. , p. 64
Keywords [sv]
Optisksortering, optisk sopsortering, sopsortering, spiralkoder, spiralteknik
National Category
Engineering and Technology
Identifiers
URN: urn:nbn:se:hh:diva-40486OAI: oai:DiVA.org:hh-40486DiVA, id: diva2:1347742
External cooperation
Halmstads Energi och Miljö AB; Bigsafe Technology AB
Subject / course
Computer science and engineering; Mechatronics
Educational program
Computer Science and Engineering, 300 credits; Mechatronic Engineer, 180 credits
Supervisors
Examiners
Available from: 2019-09-04 Created: 2019-09-02 Last updated: 2019-09-04Bibliographically approved

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  • apa
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