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Erschienen in:
2011 | OriginalPaper | Buchkapitel
Decoding 1-D Barcode from Degraded Images Using a Neural Network
verfasst von : A. Zamberletti, I. Gallo, M. Carullo, E. Binaghi
Erschienen in: Computer Vision, Imaging and Computer Graphics. Theory and Applications
Verlag: Springer Berlin Heidelberg
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Today we know that billions of products carry the 1-D bar codes, and with the increasing availability of camera phones, many applications that take advantage of immediate identification of the barcode are possible. The existing open-source libraries for 1-D barcodes recognition are not able to recognize the codes from images acquired using simple devices without autofocus or macro function. In this article we present an improvement of an existing algorithm for recognizing 1-D barcodes using camera phones with and without autofocus. The multilayer feedforward neural network based on backpropagation algorithm is used for image restoration in order to improve the selected algorithm. Performances of the proposed algorithm were compared with those obtained from available open-source libraries. The results show that our method makes possible the decoding of barcodes from images captured by mobile phones without autofocus.