基于图像分析的显微视觉照明自动优化

Automatic Illumination Optimum Techniques in Microscopic Vision Based on Image Analysis

针对手工调节照明强度、人为评测图像质量给全自动微装配/微操作带来功能局限,本文从图像高频信息分析(IHFA)的角度提出图像质量评测方法。该方法利用基于时域的梯度函数或基于频域的傅里叶变换对图像的高频能量进行计算,从而实现最佳照明强度寻优。开发了照明自动调控系统,并以此硬件为基础进行显微视觉照明实验。实验表明,图像平均亮度相应变化的平均线性度可达1.3%;在适当的照明强度下,显微图像的高频信息最大;另外,传统的图像质量评价(IQA)体系侧重于评测人类视觉感知的效果,而基于IHFA的测度函数则更好地反映了图像的信息传感功能。

Manual adjustment of lighting intensity to achieve high-quality images brought about functional limitations in fully automatic micro-assembly and micro-manipulation. An illumination optimum method based on image analysis in spatial domain or frequency domain was presented. An illumination auto adjustment system was designed and realized to test and solve above issues. Linearity of image average grayscale under the adjustment can reach 1.3%. This paper firstly proposed image quality assessment operators based on high frequency of microscopic images. Illumination intensity can be adjusted automatically by ways of image analysis. Illumination evaluation fimctions Acon_Tam and Astd were presented. Experimental results show that the correct illumination configurations are especially important for high resolution microscope and the quality of illumination directly affects the accuracy and repeatability of micromanipulation.