Bilgisayar tabanlı bir barkod okuma sistemi

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2008

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Department of Electrical & Electronics Engineering
Department of Electrical and Electronics Engineering (EE) offers solid graduate education and research program. Our Department is known for its student-centered and practice-oriented education. We are devoted to provide an exceptional educational experience to our students and prepare them for the highest personal and professional accomplishments. The advanced teaching and research laboratories are designed to educate the future workforce and meet the challenges of current technologies. The faculty's research activities are high voltage, electrical machinery, power systems, signal and image processing and photonics. Our students have exciting opportunities to participate in our department's research projects as well as in various activities sponsored by TUBİTAK, and other professional societies. European Remote Radio Laboratory project, which provides internet-access to our laboratories, has been accomplished under the leadership of our department with contributions from several European institutions.

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Bu çalışmada, değişik kameralarla elde edilmiş ürün imgelerinde barkod bilgisinin tanımlanması üzerinde durulmaktadır. Barkod bilgisinin tanımlanması için ilk olarak Barkod yerseniminin elde edilmesi gerekmektedir. Barkod yersenimi için, genellikle doğru bulmada kullanılan Hough dönüşümüne hızlı bir yaklaşıklık geliştirilmiştir. Geliştirilen bu yöntem kullanılarak barkod yersenimi ve barkod'a ait açısal yönelim bilgisi elde edilmiştir. Barkod bilgisinin okunmasında ise, barkod'a ait yersenim ve açısal yönelim bilgileri kullanılarak elde edilen tarayıcı doğru kullanılmaktadır. Ancak, Çubuk kod bilgisinin doğru okunabilmesi için imge çözünürlüğünün yeterince iyi olması gerekmektedir. Bu çalışmada, görüntü kalitesi B-spline yumuşatma ve süper çözünürlük teknikleri ile iyileştirilmektedir. Daha sonra uyuşma filtresi uygulanarak barkod bilgisi çözümlenmiştir. Barkod okuma sistemi test edilmekte ve test sonuçları tartışılmaktadır.
This study focuses on barcode recognition from images of barcode stamped products, acquired by different cameras. First step in recognition of barcode data is achieving barcode localization. For this purpose, a Fast Hough Transform Approximation has been developed. With this method, barcode localization and the angular orientation of the barcode is obtained. In order to decipher barcode data, the scan line obtained by barcode localization and angular orientation information are used. However, the image resolution has to be good enough so that the bar code data could be read properly. In this work, image quality is improved with methods of B-Spline Smoothing and super-resolution techniques. Later, barcode data is deciphered via match filtering. The proposed barcode reading system is tested and results are discussed.

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Elektrik ve Elektronik Mühendisliği, Electrical and Electronics Engineering, Barkod, Barcode

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79