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|Title:||Recovery of the distorted barcodes for mobile applications||Authors:||Lin, Dongli.||Keywords:||DRNTU::Engineering::Electrical and electronic engineering::Electronic systems::Signal processing||Issue Date:||2009||Abstract:||Barcodes have been widely used in business for their fast information acquisition capability and large information storage capacity. As technology advances, almost all mobile phones are embedded with camera devices, and these devices can be used for barcode symbol recognition, typical examples of the barcodes are EAN barcode, PDF417 and QR-code. However, the barcode images produced by the camera phones have undergone serious distortions such that it has created troubles in subsequent barcode decoding process. There are various reasons that can cause the degradation of the barcode images, which include camera noise, motion blur caused by relative motion between camera and object, defocus blur, environmental lightings and many others. In this project, the aim is to investigate the various distortions introduced in the barcode capturing process and propose effective methods to rectify the distortions. We shall focus on a typical barcode symbol, PDF417. Two sequential image blur reduction algorithms for mobile phones will be studied . The first algorithm operates on low-exposure image, which shifts the image’s brightness to the brighter side. The second algorithm enhances the blurred image contrast. Further image processing methodology on how to achieve better image quality and improvements improving in the success rate of decoding will be investigated and discussed in this report.||URI:||http://hdl.handle.net/10356/17889||Rights:||Nanyang Technological University||Fulltext Permission:||restricted||Fulltext Availability:||With Fulltext|
|Appears in Collections:||EEE Student Reports (FYP/IA/PA/PI)|
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