Asymmetry robust centroid localization in confocal microscopy

Cheng, Chen; Chai, Changchun; Liu, Xiaojun; Jiang, Xiangqian; Lu, Wenlong

doi:10.1364/ol.455938

Cited by 5 publications

(2 citation statements)

References 16 publications

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“…Therefore, these methods are robust and accurate, but complex and inefficient. The other algorithm is the centroid algorithm (CA), including the traditional centroid algorithm [16] and various improvements [17][18][19]. CA operates directly on the raw SPD data without fitting, offering significant efficiency.…”

Section: Introductionmentioning

confidence: 99%

Enhancing precision of chromatic confocal measurement through linear interpolation based centroid algorithm

Lu,

Dai,

Zeng

et al. 2024

Surf. Topogr.: Metrol. Prop.

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In chromatic confocal measurement (CCM), the accuracy and precision of the results rely on the robustness of the spectral power distribution (SPD) signal resolution. However, traditional centroid algorithms struggle with the inherent discretization of the SPD signal, leading to significant measurement errors. To address this issue, a linear interpolation based centroid algorithm is proposed to improve the robustness of the results. In the precision calibration experiment conducted with the in-house developed chromatic confocal sensors, the proposed algorithm demonstrates good robustness. Moreover, it achieves a 50% enhancement in the accuracy of a 4 mm range, improving from 1µm to 0.5µm.

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Section: Introductionmentioning

confidence: 99%

Enhancing precision of chromatic confocal measurement through linear interpolation based centroid algorithm

Lu,

Dai,

Zeng

et al. 2024

Surf. Topogr.: Metrol. Prop.

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show abstract

“…Furthermore, signal filtering can lead to a loss of information. A further algorithm that handles asymmetrical depth response signals based on the centroid method is introduced by Chen et al (2022). However, this algorithm can be insufficient in determining the exact peak location and thus probably may lead to systematic deviations in height determination, for example, in the case of layer thickness measurements, where signals from different interfaces may be more or less asymmetric (see Section 3.4).…”

Section: Introductionmentioning

confidence: 99%

A novel cubic‐exp evaluation algorithm considering non‐symmetrical axial response signals of confocal microscopes

Hagemeier,

Pahl,

Breidenbach

et al. 2023

Microscopy Res & Technique

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The depth discrimination in confocal microscopy is based on the digital analysis of depth response signals obtained by each camera pixel during measurement. Various signal‐processing algorithms are used for this purpose. The accuracy of these algorithms is inter alia restricted by the axial symmetry of the signals. However, in practice response signals are rather asymmetrical especially in case of measurement objects with critical surface structures such as edges or steep flanks. We present a novel signal‐processing algorithm based on an exponential function with a cubic argument to handle asymmetrical and also symmetrical depth response signals. Results obtained by this algorithm are compared to those of commonly used signal processing algorithms. It turns out that the novel algorithm is more robust, more accurate and exhibits a repeatability of a similar order compared to other algorithms. Research Highlights A novel, more robust algorithm with improved accuracy in peak extraction especially for asymmetrical response signals in confocal microscopy is introduced and validated. Improved accuracy is demonstrated for height and layer thickness measurements.

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Nonlinear error compensation algorithm for signal resolution of chromatic confocal measurements

Dai,

Zeng,

Zhong

et al. 2024

Measurement

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Asymmetry robust centroid localization in confocal microscopy

Cited by 5 publications

References 16 publications

Enhancing precision of chromatic confocal measurement through linear interpolation based centroid algorithm

Enhancing precision of chromatic confocal measurement through linear interpolation based centroid algorithm

A novel cubic‐exp evaluation algorithm considering non‐symmetrical axial response signals of confocal microscopes

Nonlinear error compensation algorithm for signal resolution of chromatic confocal measurements

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