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一种改进的QR码图像二值化算法 被引量:9

Improved binaryzation algorithm of modified QR code image
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摘要 对光照不均的QR码图像进行全局二值化处理后,会出现全白或全黑的误差区域,在局部二值化过程中会出现伪边界情况,并且计算时间也会变长。针对光照不均的QR码图像提出了一种改进的基于背景灰度的二值化算法。首先,根据二维码源图像大小进行分块处理,使用灰度估算公式对分块的灰度值进行计算。其次,使用联合插值算法产生背景灰度水平图像,然后用背景灰度水平图像替代源图像得到校正图像。最后,采用Ostu算法对校正图像进行二值化。实验结果表明,该算法能有效的校正光照不均的QR图像,并得到一个良好的二值化图像。 All white or all black error areas would occur to QR code image with uneven illumination after global binariza-tion processing. Pseudo-boundary would appear in the processing of local binarization,and the calculation time would be long. Aiming at the nonuniform illumination QR code image,an improved binarization algorithm is proposed,which is based on back-ground gray-level. Firstly,doing sub-block according to the size of the Qrcode image,and gray-level estimation formula is used for computing the gray-level value of each block. Secondly,joint interpolation algorithm is adopted to create the background gray-level image which is used to take the place of original image to get the corrected image. Finally,the Ostu algorithm is used for the corrected image binarization. Experiment result shows that the algorithm can effectively correct the uneven illumination QR code image and obtain a good binary image.
出处 《现代电子技术》 2014年第7期56-58,共3页 Modern Electronics Technique
关键词 QR码 二值化 图像处理 灰度值 QR code binarization image processing gray level
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  • 1朱淼良,姚远,蒋云良.增强现实综述[J].中国图象图形学报(A辑),2004,9(7):767-774. 被引量:211
  • 2蔡健荣,赵杰文.自然场景下成熟水果的计算机视觉识别[J].农业机械学报,2005,36(2):61-64. 被引量:49
  • 3Jagroop K D, Mahanan R. A review of degraded document image binarization techniques[J]. International Journal of Advanced Research in Computer and Communication Engineering, 2014,3 (5) :6582-6586.
  • 4Howe N R. Document binarization with automatic parameter tuning[J]. International Journal on Document Analysis and Re- cognition, 2013,16 ( 3 ) : 247-258.
  • 5Singh T R, Roy S, Singh O l, et al. A new local adaptive thre- sholding technique in binarization[J]. International Journal of Computer Science Issues,2011,8(6).,271-277.
  • 6Nafchi H Z, Moghaddam R F, Cheriet M. Historical document hinarization based on phase information of images[C]//Compu- ter Vision-ACCV 2012 Workshops. Springer Berlin Heidelberg, 2013:1-12.
  • 7Valizadeh M,Armanfard N, Komeili M,et al. A novel hybrid al- gorithm for binarization of badly illuminated document images [C]//14th International Computer Conference on CSI (CSICC 2009). IEEE, 2009 .. 121-126.
  • 8Burgoyne J A,Pugin L, Eustace G, et al. A comparative survey of image binarisation algorithms for optical recognition on de- graded musical sources[C]//International Society for Music In- formation Retrieval Conference (ISMIR). 2007 : 509-512.
  • 9Sauvola J, Seppanen T, Haapakoski S, et al. Adaptive document binarization[C] // Proceedings of the Fourth International Con- ference on Document Analysis and Recognition(ICDAR). IEEE. 1997.,147-152.
  • 10Vigliersoni G, Burlct G, Fujinga I. Optical measure recognition in common music notation[C]//Proceedings of International Symposium/Conference on Music Information Retrieval (IS MIR). 2013 : 125-130.

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