A conditioned level-set method with block-division strategy to flame front extraction based on OH-PLIF measurements

A novel approach to extract flame fronts, which is called the conditioned level-set method with block division （CLSB）, has been developed. Based on a two-phase level-set formulation, the conditioned initialization and region-lock optimiza-tion appear to be beneficial to improve the efficiency and accuracy of the flame contour identification. The original block- division strategy enables the approach to be unsupervised by calculating local self-adaptive threshold values autonomously before binarization. The CLSB approach has been applied to deal with a large set of experimental data involving swirl- stabilized premixed combustion in diluted regimes operating at atmospheric pressures. The OH-PLIF measurements have been carried out in this framework. The resulting images are, thus, featured by lower signal-to-noise ratios （SNRs） than the ideal image; relatively complex flame structures lead to significant non-uniformity in the OH signal intensity; and, the mag- nitude of the maximum OH gradient observed along the flame front can also vary depending on flow or local stoichiometry. Compared with other conventional edge detection operators, the CLSB method demonstrates a good ability to deal with the OH-PLIF images at low SNR and with the presence of a multiple scales of both OH intensity and OH gradient. The robustness to noise sensitivity and intensity inhomogeneity has been evaluated throughout a range of experimental images of diluted flames, as well as against a circle test as Ground Truth （GT）.

A conditioned level-set method with block-division strategy to flame front extraction based on OH-PLIF measurements

A novel approach to extract flame fronts, which is called the conditioned level-set method with block division(CLSB),has been developed. Based on a two-phase level-set formulation, the conditioned initialization and region-lock optimization appear to be beneficial to improve the efficiency and accuracy of the flame contour identification. The original blockdivision strategy enables the approach to be unsupervised by calculating local self-adaptive threshold values autonomously before binarization. The CLSB approach has been applied to deal with a large set of experimental data involving swirlstabilized premixed combustion in diluted regimes operating at atmospheric pressures. The OH-PLIF measurements have been carried out in this framework. The resulting images are, thus, featured by lower signal-to-noise ratios(SNRs) than the ideal image; relatively complex flame structures lead to significant non-uniformity in the OH signal intensity; and, the magnitude of the maximum OH gradient observed along the flame front can also vary depending on flow or local stoichiometry.Compared with other conventional edge detection operators, the CLSB method demonstrates a good ability to deal with the OH-PLIF images at low SNR and with the presence of a multiple scales of both OH intensity and OH gradient. The robustness to noise sensitivity and intensity inhomogeneity has been evaluated throughout a range of experimental images of diluted flames, as well as against a circle test as Ground Truth(GT).