Real-Time Curvature Defect Detection on Outer Surfaces Using Best-Fit Polynomial Interpolation

Golkar, Ehsan; Prabuwono, Anton Satria; Patel, Ahmed

doi:10.3390/s121114774

Cited by 10 publications

(4 citation statements)

References 18 publications

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“…For particle detection, the curvature function of surface or plane curves can be used. However, conventional methods for the curvature computation use derivatives; thus, the field of their application is limited to smooth surfaces [40]. Therefore, the development of new methods for the computation of the curvature of the SPMimages considering their peculiar features is of high practical value.…”

Section: Detection Of Particles Using the Surface Curvature Functionmentioning

confidence: 99%

Particle and Particle Agglomerate Size Monitoring by Scanning Probe Microscope

et al. 2022

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In the present study, the use of a scanning probe microscope is described for monitoring the sizes of nanoparticles. Monitoring is the process of acquiring and analysing the set of overlapping images. The main analysis steps are image segmentation, determination of nanoparticles allocation and their sizes, determination of the overlap of images with one another, and exclusion of repeating measurements for the formation of the correct particle-size sampling. The thorough examination of commercial scanning probe microscopes, software, and image processing libraries showed that their capabilities are limited for image segmentation and determination of sizes in complex structured images. A method based on the surface curvature computation is proposed for the image segmentation (allocation of particles) and determination of particle sizes. The curvature is estimated using the surface area approximation with respect to the circumference. It is proposed to use sample displacement sensors as an aid for image stitching.

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Section: Detection Of Particles Using the Surface Curvature Functionmentioning

confidence: 99%

Particle and Particle Agglomerate Size Monitoring by Scanning Probe Microscope

et al. 2022

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“…However, the industry needs to quantitatively differentiate the mirror-finished surfaces among diverse products. The mirror-finished surface topography is the most important surface geometry and physical property for mirror-finished components [14]. An in-situ surface-topography measurement system is crucial to reducing rejections and costs.…”

Section: Introductionmentioning

confidence: 99%

Surface Topography Measurement of Mirror-Finished Surfaces Using Fringe-Patterned Illumination

Fang

Tjahjowidodo

2020

Metals

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Mirror-finished surface products have a wide range of applications in different engineering industries, such as power generation, aerospace, semiconductors and optics. The surface topography of mirror-finished products is typically measured in a metrology laboratory, which is typically time consuming and cannot be integrated into the manufacturing process. To allow for in-situ product quality assurance and automatic tool change for manufacturing processes, a more accurate and responsive surface-measurement method is needed. For highly polished surfaces, a sub-micron surface fluctuation makes it possible to use light-scattering effects and image processing for surface texture analysis. A non-contact surface inspection system using a fringe-patterned illumination method is proposed in this paper. A predesigned pattern was projected onto the target surface, and its reflected image was captured by a camera. It was found that the surface parameters Sa and Sq, which are widely used to evaluate surface quality, are significantly correlated with luminous-intensity distribution. Another parameter, Str, which quantifies the uniformity of surface-texture directions due to polishing or grinding marks, was traditionally quantified after a complete-surface topographic measurement. In this research, a new approach is proposed to determine surface isotropy through a luminance-intensity distribution analysis. By rotating the test coupon, the variation of specular reflection showed correlation with the significance of surface-texture direction. The experimental results demonstrate that mirror-finished surfaces with a large deviation in luminance intensity across the pattern possess low Str values, which indicates low uniformity in surface texture.

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“…The paper [1] describes a framework for steel surface defects detection and classification using Scale Invariant Feature Transform for defects detection. The paper [2] presents a novel, real-time defect detection system, based on a best-fit polynomial interpolation, which inspects the conditions of outer surfaces. In this paper a method based on Dual-Tree Complex Wavelet Transform (DT-CWT) was proposed to inspection of cold rolled steel sheets for detection and classification of surface defects.…”

Section: Introductionmentioning

confidence: 99%

Image Enhancement Method for Steel Surface Defects Based on DT-CWT

Chen

Wang

Xie

2013

AMM

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A method based on Dual-Tree Complex Wavelet Transform (DT-CWT) was proposed for enhancing the images. By taking into account the non-Gaussian probability distribution and the statistical dependencies among wavelet coefficients of some signals, and by taking advantage of near shift-invariance of DT-CWT, it can obtain higher signal-to-noise ratio (SNR) than common wavelet denoising methods. The simulation results show that the proposed method is better than the traditional methods. It has a good enhancement performance which can improve the details of the image automatically.

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Real-Time Curvature Defect Detection on Outer Surfaces Using Best-Fit Polynomial Interpolation

Cited by 10 publications

References 18 publications

Particle and Particle Agglomerate Size Monitoring by Scanning Probe Microscope

Particle and Particle Agglomerate Size Monitoring by Scanning Probe Microscope

Surface Topography Measurement of Mirror-Finished Surfaces Using Fringe-Patterned Illumination

Image Enhancement Method for Steel Surface Defects Based on DT-CWT

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