An improved γ-CLAHE image enhancement algorithm for dot matrix invisible code

Mingyang Ren, Jiangfeng Xu
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Abstract

Dot matrix invisible code is widely used in anti-counterfeiting and traceability of goods, dot matrix invisible code is a kind of technology that "disappears" in the package decoration. This kind of code will neither destroy the overall effect of packaging decoration nor affect the function of barcode, it provide technical support for anti-counterfeit traceability means, which is difficult to be seen by the naked eye and needs to be read under special lighting conditions, merchants and consumers can access product information by identifying the code, it often has the problem of poor contrast due to light intensity, shooting angle and other reasons. The image enhancement technology is used to improve the image quality and lay the foundation for the subsequent work. This paper proposes an improved γ-CLAHE image enhancement algorithm for dot matrix invisible code, which converts the image into the color space with color and brightness separation, performs histogram equalization enhancement processing on the brightness components, combines with Gamma correction, so that the enhanced image quality is significantly improved. In this study, the CLAHE algorithm and the improved algorithms on LAB, HSV and YCrCb color spaces are compared separately, the experimental results show that the improved algorithm is much more effective than the CLAHE algorithm, and the improved algorithm in YCrCb color space is more suitable for image enhancement of dot matrix invisible codes than other color and bright separation color spaces, It has obvious superiority in indicators such as information entropy, mean gradient, standard deviation, etc., and can effectively improve the contrast of low-quality dot matrix invisible codes, at the same time, this study provide ideas for similar invisible code image enhancement.
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一种改进的γ-CLAHE点阵不可见码图像增强算法
点阵隐形码广泛应用于商品的防伪溯源,点阵隐形码是一种在包装装潢中“消失”的技术。这种条码既不会破坏包装装饰的整体效果,也不会影响条码的功能,它为防伪溯源手段提供了技术支持,在特殊的照明条件下很难被肉眼看到,需要读取,商家和消费者可以通过识别条码获取产品信息,由于光线强度、拍摄角度等原因,往往存在对比度较差的问题。采用图像增强技术提高图像质量,为后续工作奠定基础。本文提出了一种改进的针对点阵不可见码的γ-CLAHE图像增强算法,该算法将图像转换为色彩与亮度分离的色彩空间,对亮度分量进行直方图均衡化增强处理,并结合Gamma校正,使增强后的图像质量得到明显提高。本研究分别对LAB、HSV和YCrCb色彩空间上的CLAHE算法和改进算法进行了比较,实验结果表明,改进算法比CLAHE算法有效得多,而且YCrCb色彩空间上的改进算法比其他色彩和明暗分离色彩空间更适合于点矩阵不可见码的图像增强,在信息熵、平均梯度、并能有效提高低质量点阵不可见码的对比度,同时,本研究为类似不可见码的图像增强提供思路。
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