Application of Conditioned Level-Set Method to OH-PLIF Image Processing of Typical Molecule Diffusion Flames

Yue Han, Nanjia Yu, J. Dai, Guobiao Cai
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引用次数: 1

Abstract

A novel approach for OH-PLIF image processing, namely conditioned level-set (CLS) method, is presented in this paper. The complete CLS method consists of raw image pre-processing, adaptive intensity shareholding for linearization, initial contour extraction, region-lock optimization and level set iteration. The successful application of this method to typical molecule diffusion flames demonstrates its robustness to noise sensitivity and flame topology, and its outperformance over traditional edge detectors in terms of flame contour identification. The CLS method provides possibility to further image analysis such as mean reaction zone tracking. Based on the results from RANS simulation with adequate modelling, a novel numerical-aided approach for concentration calibration is also proposed. The CLS method can readily be employed to experimental images obtained from other planar scalar measurements. The proposed method has potential to be integrated to image processing modules of scientific software.
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条件水平集法在典型分子扩散火焰OH-PLIF图像处理中的应用
本文提出了一种用于OH-PLIF图像处理的新方法,即条件水平集(CLS)方法。完整的CLS方法包括原始图像预处理、线性化自适应强度分配、初始轮廓提取、区域锁定优化和水平集迭代。对典型分子扩散火焰的成功应用表明,该方法对噪声敏感性和火焰拓扑结构具有鲁棒性,在火焰轮廓识别方面优于传统的边缘检测器。CLS方法为进一步的图像分析提供了可能,如平均反应区跟踪。在充分建模的RANS模拟结果的基础上,提出了一种新的数值辅助浓度校准方法。CLS方法可以很容易地应用于其他平面标量测量得到的实验图像。该方法具有集成到科学软件图像处理模块中的潜力。
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