摘要
结合测量误差分析理论,提出一种新的高效的图像分割算法,将薄膜的连续图像采样过程看做等精度测量过程,背景图像认为仅存在随机误差,缺陷像素视做粗大误差。算法在起始阶段通过连续多次采样建立标准背景图像,并统计各像素位置的灰度标准差,然后将实时待测图像中的每个像素与标准背景像素进行减法运算,以3σ作为检测判据,从而将缺陷的检测与分离等效为粗大误差的判别与剔除问题;同时,考虑缺陷像素点的空间分布特征,将上述过程扩展到像素邻域范围,以二维分割阈值取代一维阈值,对离散噪声有明显的抑制作用。实验结果表明,该算法运算速度快,对低对比度图像适应性好,对噪声不敏感,可实现对不同种类缺陷的准确、完整分割,适于实时光学薄膜检测应用。
Based on error correction theory,this paper proposed a novel algorithm to inspect defects rapidly.With an assumption that only random errors existed in a background image in which the random errors followed a normal distribution,the defect inspection problem converted to a gross error correcting problem,which could be solved naturally by using the 3σ rule.The algorithm applied 2D thresholds generated from neighbor pixels to reduce the influence of noise.A comparison of the computational results with the existing methods indicates that the proposed algorithm is a viable alternative for image segmentation in defect inspection applications.
出处
《计算机应用研究》
CSCD
北大核心
2012年第4期1575-1577,共3页
Application Research of Computers
基金
中央高校基本科研业务费专项资金资助项目(2009ZM0043)
高等学校博士学科点专项科研基金资助课题(200805611088)
关键词
图像分割
误差修正
光学薄膜
缺陷检测
image segmentation
error correction
optical films
defect inspection
