Surface measurement using active vision and light scattering

Tian, Gui Yun; Lu, Rong; Gledhill, Duke

doi:10.1016/j.optlaseng.2006.03.005

Cited by 68 publications

(24 citation statements)

References 52 publications

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“…As a result of the research undertaken it was possible to get a range of surface roughness very similar to the one described in the work [20]. The results of the subsequent work carried out using the system are presented by G. Y. Tian, R. S. Lu and D. Gledhill [29], while the experimental setups, based on similar methods are discussed in [30,31].…”

Section: Using Scattered Light For In-process Inspectionmentioning

confidence: 89%

Laser methods based on an analysis of scattered light for automated, in-process inspection of machined surfaces: A review

Kapłonek

Nadolny

2015

Optik

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Section: Using Scattered Light For In-process Inspectionmentioning

confidence: 89%

Laser methods based on an analysis of scattered light for automated, in-process inspection of machined surfaces: A review

Kapłonek

Nadolny

2015

Optik

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“…Surface morphology presents some single regular triangles characteristic of <111> crystallographic orientation as well as many irregular shapes, which contributes to poor smoothness (Rq = 76 nm). Parameter Rq has been determined by total integrated scattering (TIS) method [21][22][23] using laser scatterometer type SL 31 produced by Polish Institute of Mathematical Machines, Warsaw [23]. The Rq parameter is the value of mean square deviation of surface roughness profile.…”

Section: Experiments With Mbe/mocvd Buffer Layersmentioning

confidence: 99%

Surface smoothness improvement of HgCdTe layers grown by MOCVD

Madejczyk¹,

Piotrowski²,

Kłos³

et al. 2009

Bulletin of the Polish Academy of Sciences: Technical Sciences

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Abstract. This paper presents results of experimental efforts pointed towards morphology improvement of HgCdTe layers grown by MOCVD on GaAs substrates. Selected growth parameters on morphology state are presented. The substrate issues like its quality and crystallographic orientation have been discussed. Also influence of HgCdTe layer thickness on its surface roughness is described.It is shown that extensive characterization studies using accessible equipments and methods: atomic force microscopy (AFM), secondary electron microscopy (SEM), laser scatterometer and Nomarski microscopy, have provided invaluable information about the correlation between defect formation and the influence of specific growth parameters.

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“…Several studies have been performed to inspect the surface roughness of a part based on image processing. These introduced techniques include light scattering [3][4][5][6], laser speckle [7][8][9], and several types of texture analysis [10,11,12].…”

Section: Introductionmentioning

confidence: 99%

Surface roughness inspection in milling operations with photometric stereo and PNN

Kaya

2015

Int J Adv Manuf Technol

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Offline human-assisted surface quality inspection techniques are time-consuming and need labor intensive setup requirements that are sometimes unacceptable due to their slowing down of manufacturing productivity. This paper proposes an efficient surface roughness inspection method which uses photometric stereo and probabilistic neural network (PNN). A photometric stereo scheme with six images was used to generate a 3D depth map of the machined surface. Probabilistic neural network and statistical features extracted from the depth map were employed for the classification of surface roughness quality. The method was validated on several machined surfaces with different surface roughnesses. The satisfying accuracy of the introduced method demonstrates the feasibility of the proposed system.

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Surface measurement using active vision and light scattering

Cited by 68 publications

References 52 publications

Laser methods based on an analysis of scattered light for automated, in-process inspection of machined surfaces: A review

Laser methods based on an analysis of scattered light for automated, in-process inspection of machined surfaces: A review

Surface smoothness improvement of HgCdTe layers grown by MOCVD

Surface roughness inspection in milling operations with photometric stereo and PNN

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