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http://dx.doi.org/10.6109/jkiice.2016.20.1.58

Robust k-means Clustering-based High-speed Barcode Decoding Method to Blur and Illumination Variation  

Kim, Geun-Jun (Department of Electronic Engineering, Dong-A University)
Cho, Hosang (Department of Electronic Engineering, Dong-A University)
Kang, Bongsoon (Department of Electronic Engineering, Dong-A University)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.20, no.1, 2016 , pp. 58-64 More about this Journal
Abstract
In this paper presents Robust k-means clustering-based high-speed bar code decoding method to blur and lighting. for fast operation speed and robust decoding to blur, proposed method uses adaptive local threshold binarization methods that calculate threshold value by dividing blur region and a non-blurred region. Also, in order to prevent decoding fail from the noise, decoder based on k-means clustering algorithm is implemented using area data summed pixel width line of the same number of element. Results of simulation using samples taken at various worst case environment, the average success rate of proposed method is 98.47%. it showed the highest decoding success rate among the three comparison programs.
Keywords
Barcode Decoder; Binarization; High Pass Filter; Image Processing;
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