An Instrument for the Geometric Attributes of Metallic Appearance

Christie, John S.

doi:10.1364/ao.8.001777

Cited by 9 publications

(5 citation statements)

References 1 publication

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“…In addition to three "optical" axes for fast laser beam movement, five mechanical axes (three linear and two rotatory) are used for positioning of the work piece relatively to the laser scanning system. This experimental setup enables 5 + 3 axes laser processing of work pieces with maximal dimensions of 300 × 300 × 100 mm 3 within an inert gas atmosphere [5].…”

Section: Set-upmentioning

confidence: 99%

“…The gloss thereby reflects one of the most important properties of a surface when it comes to evaluate the visual appearance . The geometric attributes of gloss or the reflection of light on a surface are usually divided into eight different characteristics . A common way to evaluate the gloss of a surface is by measurement of the specular gloss, which describes the intensity ratio of directly reflected light compared to the incident light.…”

Section: Introductionmentioning

confidence: 99%

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Design surfaces by laser remelting

Temmler

Willenborg

Wissenbach

2015

Materialwissenschaft Werkst

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Molds and dies are used today in the manufacturing of a wide range of industrial products. They have a broad field of applications from the air and space technology, the automotive sector, to electrical engineering, to household products and consumer goods. The surface of a part or product strongly influences its properties and functions e.g. it's visual appearance. The gloss thereby reflects one of the most important properties of a surface when it comes to evaluate the visual appearance. Therefore, among others, in this paper the influence of laser polishing on the generated specular gloss is investigated for the hot work steel 1.2343 (AISI: H11). On the one hand laser polished surfaces are measured by WLI and investigated by a spectral analysis of surfaces roughness. A spectral analysis is achieved by a discrete convolution of the surface profile with a Gaussian loaded function similar to ISO 11562. On the other hand specular gloss measurements were carried out at 20°, 60° and 85°. For the experiments a fiber‐coupled solid state disc laser (Yb : YAG; Q‐switched) is used (PL,max = 550 W; repetition frequency: fP = 5–20 kHz, pulse duration: tP = 0,7–3,5 µs, pulsed and cw‐operation). In general, scanning velocity and average laser power are two crucial procedural parameters for laser polishing with significant influence on the resulting surface roughness. These procedural parameters are investigated systematically, while other procedural parameters, such as laser beam diameter dL = 250 µm and track offset dy = 25 µm were kept constant. By this a significant reduction of roughness was achieved, especially for the wavelength interval λ < 320 µm. A correlation between specular gloss of surfaces and the measured micro‐roughness is carried out. In order to make a systematic classification laser polished fields are compared to surfaces which were prepared by conventional mechanical manufacturing processes, such as turning, milling, grinding, high end manual polishing etc. Specular gloss shows a good exponential correlation with micro‐ and meso‐roughness were as macro roughness shows no significant influence on the specular gloss. Additionally, a complete process chain for selectively laser polishing of metallic surfaces was developed in order to apply different levels of gloss onto free formed work pieces. Selective laser polishing and the process chain are demonstrated for a free formed tool insert with leather textured surface, where only the indentations of the leather texture were laser polished selectively

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Section: Set-upmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Design surfaces by laser remelting

Temmler

Willenborg

Wissenbach

2015

Materialwissenschaft Werkst

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“…A sizable economic value is placed on the visual appearance of metallic surfaces in sectors such as the automotive and jewelry industries, and the literature on metallic appearance reflects this. There are numerous studies quantifying and perceptually evaluating the visual qualities of metallic surfaces and coatings, considering qualities such as colour, gloss 7 , scatter, brilliance, and lustre 8 , as well as ‘visual texture’ such as glitter, glint, and sparkle 9 , 10 . Recently, attention has focused more on how the physical properties of objects and their lighting environment might give rise to a metallic appearance 11 – 13 .…”

Section: Introductionmentioning

confidence: 99%

Low level visual features support robust material perception in the judgement of metallicity

Harvey

Smithson

2021

Sci Rep

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The human visual system is able to rapidly and accurately infer the material properties of objects and surfaces in the world. Yet an inverse optics approach—estimating the bi-directional reflectance distribution function of a surface, given its geometry and environment, and relating this to the optical properties of materials—is both intractable and computationally unaffordable. Rather, previous studies have found that the visual system may exploit low-level spatio-chromatic statistics as heuristics for material judgment. Here, we present results from psychophysics and modeling that supports the use of image statistics heuristics in the judgement of metallicity—the quality of appearance that suggests an object is made from metal. Using computer graphics, we generated stimuli that varied along two physical dimensions: the smoothness of a metal object, and the evenness of its transparent coating. This allowed for the exploration of low-level image statistics, whilst ensuring that each stimulus was a naturalistic, physically plausible image. A conjoint-measurement task decoupled the contributions of these dimensions to the perception of metallicity. Low-level image features, as represented in the activations of oriented linear filters at different spatial scales, were found to correlate with the dimensions of the stimulus space, and decision-making models using these activations replicated observer performance in perceiving differences in metal smoothness and coating bumpiness, and judging metallicity. Importantly, the performance of these models did not deteriorate when objects were rotated within their simulated scene, with corresponding changes in image properties. We therefore conclude that low-level image features may provide reliable cues for the robust perception of metallicity.

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“…A sizable economic value is placed on the visual appearance of metallic surfaces in sectors such as the automotive and jewelry industries, and the literature on metallic appearance reflects this. There are numerous studies quantifying and perceptually evaluating the visual qualities of metallic surfaces and coatings, considering qualities such as colour, gloss 7 , scatter, brilliance, and lustre 8 , as well as 'visual texture' such as glitter, glint, and sparkle 9,10 . Recently, attention has focused more on how the physical properties of objects and their lighting environment might give rise to a metallic appearance [11][12][13] .…”

Section: Introductionmentioning

confidence: 99%

Modeling Metallicity: Low Level Visual Features Support Robust Material Perception

Harvey

Smithson

2021

Preprint

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The human visual system is able to rapidly and accurately infer the material properties of objects and surfaces in the world. Yet an inverse optics approach---estimating the bi-directional reflectance distribution function of a surface, given its geometry and environment, and relating this to the optical properties of materials---is both intractable and computationally unaffordable. Rather, previous studies have found that the visual system may exploit low-level spatio-chromatic statistics as heuristics for material judgment. Here, we present results from psychophysics and modeling that supports the use of image statistics heuristics in the judgement of metallicity---the quality of appearance that suggests an object is made from metal. Using computer graphics, we generated stimuli that varied along two physical dimensions: the smoothness of a metal object, and the evenness of its transparent coating. This allowed for the manipulation of low-level image statistics, whilst ensuring that each stimulus was a naturalistic, physically plausible image. A conjoint-measurement task decoupled the contributions of these dimensions to the perception of metallicity. Low-level image features, as represented in the activations of oriented linear filters at different spatial scales, were found to correlate with the dimensions of the stimulus space, and decision-making models using these activations replicated observer performance in judging metal smoothness, coating bumpiness, and metallicity. Importantly, the performance of these models did not deteriorate when objects were rotated within their simulated scene, with corresponding changes in image properties. We therefore conclude that low-level image features may provide reliable cues for the robust perception of metallicity.

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An Instrument for the Geometric Attributes of Metallic Appearance

Cited by 9 publications

References 1 publication

Design surfaces by laser remelting

Design surfaces by laser remelting

Low level visual features support robust material perception in the judgement of metallicity

Modeling Metallicity: Low Level Visual Features Support Robust Material Perception

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