基于Matlab的暗场图像处理算法研究

Research on dark field image processing algorithm based on matlab

为了克服传统暗场图像处理误差较大、重复性较差等问题,文章提出一种暗场光谱分析算法.此算法以Matlab为平台,在暗场环境下通过图像膨胀等方法对金纳米粒子进行精确识别并计算亮度,同时考虑光谱标准化、除去污染物杂质等问题,然后重建单粒子散射峰并记录其光谱特性.金纳米棒检测实验结果表明,此算法相较于根据粒子亮度进行二值化处理的传统方法在识别粒子上更加灵活精确,粒子识别率可达91.33%,粒子拟合的准确率提升了15.59%.此算法还可以批量检测粒子在结合前后的光谱特性,数据结果与理论值相符,数据处理效果良好,为暗场图像处理领域提供了更灵活、快速、准确性高的新型算法.

In order to overcome the large error and poor repeatability of traditional dark field image processing,a dark field spectrum analysis algorithm is proposed.This algorithm uses Matlab as the platform to accurately identify gold nanoparticles and calculate the brightness through image expansion and other methods in a dark field environment.At the same time,it takes into account issues such as spectral standardization and removal of contaminants and impurities,and then reconstructs the single-particle scattering peak and records its spectrum characteristic.The experimental results of gold nanorod detection show that this algorithm is more flexible and accurate in identifying particles than the traditional method based on brightness binarization.The particle recognition rate can reach 91.33%,and the accuracy of particle fitting has increased by 15.59%.This algorithm can also detect the spectral characteristics of particles before and after the combination in batches.The data results are consistent with the theoretical values,and the data processing effect is good.It provides a more flexible,fast and accurate new algorithm for the field of dark field image processing.