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液晶显示屏 Mura缺陷是一类较难检测的显示缺陷,它具有对比度低、背景亮度不均匀、边缘模糊等特点。针对传统Chan-Vese模型(C-V模型)对其分割时存在误分割及速度慢的问题,本文提出一种改进的C-V模型。首先,依据曲线演化理论,简化了传统C-V模型的图像数据力驱动项,这样减少了迭代过程中的计算量,提高了分割的速度。其次,为了平衡图像的亮度不均匀,在模型中引入一个新的能量项,该能量项与轮廓曲线内、外部之间的亮度差有关,提高了分割的准确性。最后,在算法的实现过程中引入迭代停止的判别式,通过设定分割的精度可以实现迭代的自动停止,并有利于正确地分割出目标。实验结果表明,本文提出的改进C-V模型能够准确分割背景不均匀的 Mura缺陷,并且具有较快的速度。

LCD Mura defect is difficult to detect.It has the features of low contrast,uneven bright-ness,blurry edge,and so on.The traditional Chan-Vese model (C-V model)cannot accurately seg-ment the Mura defect and the segmentation speed is slow.In order to solve the problems,this paper presents an improved C-V model.First of all,according to the theory of curve evolution,the image data force in the traditional C-V model is simplified to reduce the iterative process of calculation and improve the segmentation speed.Secondly,in order to reduce the effect from non-uniformity bright-ness of image,the model is proved by adding a new energy term that related to the brightness differ-ence between inside and outside area of the contour curve to improve the accuracy of the segmentation. Finally,the iterative stopping criterion is introduced in the implementation process of the algorithm, the setting of the segmentation accuracy can aid both in achieving the automatic iteration stop and seg-menting the target correctly.Experimental results indicate that improved C-V model in this paper can accurately segment the background uneven Mura defect and it has a faster speed.

参考文献

[1] 李坤;李辉;刘云杰;梁平;卢小鹏.LCD Mura缺陷的B样条曲面拟合背景抑制[J].光电工程,2014(2):33-39.
[2] 刘毅;郑学仁.液晶屏显示缺陷自动检测系统的设计[J].微计算机信息,2008(19):250-251,297.
[3] Tsneg, YH;Tsai, DM.Defect detection of uneven brightness in low-contrast images using basis image representation[J].Pattern Recognition: The Journal of the Pattern Recognition Society,20103(3):1129-1141.
[4] 卢小鹏;李辉;刘云杰;梁平;李坤.基于Chan-Vese模型的TFT-LCD Mura缺陷快速分割算法[J].液晶与显示,2014(1):146-151.
[5] 毕昕;丁汉.TFT-LCD Mura缺陷机器视觉检测方法[J].机械工程学报,2010(12):13-19.
[6] 东野长磊;郑永果;姜东焕;张彬.基于全局极小解Chan-Vese模型的SAR图像分割[J].计算机工程与设计,2012(11):4255-4258.
[7] 龚劬;王迎龙;马家军.改进CV模型图像分割的Split-Bregman方法[J].计算机工程与应用,2015(6):171-175.
[8] 张开华;周文罡;张振;郑孝娟.一种改进的C-V主动轮廓模型[J].光电工程,2008(12):112-116.
[9] Weickert J.;Romeny B.M.T.H..Efficient and reliable schemes for nonlinear diffusion filtering[J].IEEE Transactions on Image Processing,19983(3):398-410.
[10] 谢强军;侯迪波;黄平捷;张光新;周泽魁.一种改进的单参数水平集快速分割方法[J].光电子·激光,2009(12):1671-1675.
[11] 李俊;杨新;施鹏飞.基于Mumford-Shah模型的快速水平集图像分割方法[J].计算机学报,2002(11):1175-1183.
[12] 朱晓舒;孙权森;夏德深.基于凸优化的自适应CV模型[J].计算机应用研究,2012(2):779-781.
[13] 葛琦;韦志辉;张建伟;冯灿;詹天明.结合改进FCM算法的多相位CV模型[J].中国图象图形学报,2011(4):547-553.
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