依据LED芯片图像构图单一,灰度不均匀的基本特征,提出了一种针对这类图像的新的局部自适应阈值分割算法,实现晶粒分割与计数统计。在阈值的设计中,一方面考虑了图像整体区域灰度特征,同时利用区域与区域中心对比度不同,设计了区域对比率来表示这一特性,通过局部均值和中心点区域对比率来自适应调整阈值的大小,识别出晶粒的准确位置。为了剔除不合格晶粒和噪音干扰,应用基于腐蚀和膨胀操作的图像形态学方法对分割后晶粒进行滤波处理,通过晶粒面积来确定有效晶粒个数。实验结果表明,本算法在晶粒计数效率和精度方面,取得了较好的结果。

According to the basic characteristics of LED chip image composition and gray scale inhomogeneity, a new local adaptive threshold algorithm was proposed for the segmentation of the LED grain. In the design of the threshold, characteristics of the gray level inhomogeneity of the image area and the contrast of the different points to the center point were considered.A regional contrast ratio is designed to represent this characteristic.The adaptive threshold adjustment was implemented in combination with both local mean and regional center contrast to identify the exact location of the LED grain.At the same time, in order to eliminate the unqualified LED grain and noise interference,the image morphology method based on corrosion and expansion operation was applied to filter the segmented images. The number of effective LED grain was determined by the LED chip size.The experimental results show that the algorithm has achieved good results in terms of grain counting efficiency and accuracy.