國立虎尾科技大學 |

The Effects of Texture on Visual and Instrumental Color Difference Assessments.

Record Type:	Language materials, manuscript : Monograph/item
Title/Author:	The Effects of Texture on Visual and Instrumental Color Difference Assessments./
Author:	Luo, Zhenhua.
Description:	1 online resource (495 pages)
Notes:	Source: Dissertations Abstracts International, Volume: 85-11, Section: B.
Contained By:	Dissertations Abstracts International85-11B.
Subject:	Experimental psychology. -
Online resource:	click for full text (PQDT)
ISBN:	9798382621944

The Effects of Texture on Visual and Instrumental Color Difference Assessments.
Luo, Zhenhua.

The Effects of Texture on Visual and Instrumental Color Difference Assessments. - 1 online resource (495 pages)

Source: Dissertations Abstracts International, Volume: 85-11, Section: B.

Thesis (Ph.D.)--North Carolina State University, 2023.

Includes bibliographical references

Surface texture stands as an essential factor influencing both perceptual and instrumental color assessments of stimuli. Its impact on color difference evaluation is of continual concern in the field of color science and holds significant industrial relevance. Typically, the effects of surface texture are accommodated by adjustable weights in color-difference formulas. These weights are commonly set at a 2:1:1 ratio for calculating color differences in textile samples, despite the appropriateness of this ratio not being well understood and validated. Furthermore, prior quantitative analyses addressing this influence have primarily focused on simple simulated textures, such as random dots or winding threads. These limited scenarios are insufficient for encompassing the wide range of textures encountered in industrial settings.To deepen our understanding of texture effects, the present study aimed to examine how knitting textures affect color difference assessments. To achieve this goal, a workflow was established for capturing images of knitted samples and accurately reproducing them on an LCD monitor. In addition, both statistical and psychophysical evaluations were conducted on a range of color-to-texture fusion methods, to determine the one that offers optimal color fidelity. The selected rendering algorithm enabled the faithful simulation of textured stimuli with user-defined target colors, thus facilitating the development of an extensive visual tolerance dataset. The dataset involved the color-difference tolerances of 26 observers for the uniform stimuli and those with 10 distinct textures, sampling around 11 color centers across the color gamut. This dataset was subsequently employed to explore the impact of various knitting textures on visual tolerances and to assess how the color-difference formulas perform in predicting the perceived color differences in the textured stimuli.The findings of this study validate the significant impact of texture on lightness, chroma, and hue tolerances, with lightness tolerances exhibiting more pronounced effects. Specific textures significantly enhance lightness tolerances when compared to uniform stimuli. This trend is also observable in chroma and hue tolerances for stimuli with specific color centers and texture patterns. Additionally, the research optimized the parametric factors for color-difference formulas (specifically, CIE94, CMC, and CIEDE2000) based on the tolerance dataset. The optimized factors ranged from 0.80 to 1.50, which cast doubts on the widely used 2:1:1 ratio. The analysis suggests that CAM16-UCS is the top performer for calculating color differences in stimuli featuring the examined knitting textures.In a secondary investigation, the study also sought to assess the influence of the dimension and shape of polymeric pellets on their instrumental colorimetric and spectral measurements, with a particular emphasis on measurement repeatability. In the experiments, a range of colorless and translucent granules underwent measurements using the spectrophotometer. Two measurement protocols were applied: bulk measurements, involving filling granules within a 50-mm pathlength glass cuvette, and single-pellet measurements, which measured individual granules against an achromatic backing. For both measurement approaches, the results indicated minimal or inconsistent effects of sample geometries on measurement repeatability. However, the granule varieties with distinct geometric parameters exhibited unique reflectance profiles and significantly varied colorimetric values, suggesting the influential role of granule geometric characteristics in color measurements.

Electronic reproduction.
Ann Arbor, Mich. :
ProQuest,
2024

Mode of access: World Wide Web

ISBN: 9798382621944Subjects--Topical Terms:

1180476
Experimental psychology.
Index Terms--Genre/Form:

554714
Electronic books.

The Effects of Texture on Visual and Instrumental Color Difference Assessments.
LDR:04925ntm a22003377 4500 001 1152433
005 20241203090553.5
006 m o d
007 cr mn ---uuuuu
008 250605s2023 xx obm 000 0 eng d
020 $a 9798382621944
035 $a (MiAaPQ)AAI30984022
035 $a (MiAaPQ)NCState_Univ18402041417
035 $a AAI30984022
040 $a MiAaPQ $b eng $c MiAaPQ $d NTU
100 1 $a Luo, Zhenhua. $3 1479423
245 1 4 $a The Effects of Texture on Visual and Instrumental Color Difference Assessments.
264 0 $c 2023
300 $a 1 online resource (495 pages)
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
338 $a online resource $b cr $2 rdacarrier
500 $a Source: Dissertations Abstracts International, Volume: 85-11, Section: B.
500 $a Advisor: Shamey, Renzo.
502 $a Thesis (Ph.D.)--North Carolina State University, 2023.
504 $a Includes bibliographical references
520 $a Surface texture stands as an essential factor influencing both perceptual and instrumental color assessments of stimuli. Its impact on color difference evaluation is of continual concern in the field of color science and holds significant industrial relevance. Typically, the effects of surface texture are accommodated by adjustable weights in color-difference formulas. These weights are commonly set at a 2:1:1 ratio for calculating color differences in textile samples, despite the appropriateness of this ratio not being well understood and validated. Furthermore, prior quantitative analyses addressing this influence have primarily focused on simple simulated textures, such as random dots or winding threads. These limited scenarios are insufficient for encompassing the wide range of textures encountered in industrial settings.To deepen our understanding of texture effects, the present study aimed to examine how knitting textures affect color difference assessments. To achieve this goal, a workflow was established for capturing images of knitted samples and accurately reproducing them on an LCD monitor. In addition, both statistical and psychophysical evaluations were conducted on a range of color-to-texture fusion methods, to determine the one that offers optimal color fidelity. The selected rendering algorithm enabled the faithful simulation of textured stimuli with user-defined target colors, thus facilitating the development of an extensive visual tolerance dataset. The dataset involved the color-difference tolerances of 26 observers for the uniform stimuli and those with 10 distinct textures, sampling around 11 color centers across the color gamut. This dataset was subsequently employed to explore the impact of various knitting textures on visual tolerances and to assess how the color-difference formulas perform in predicting the perceived color differences in the textured stimuli.The findings of this study validate the significant impact of texture on lightness, chroma, and hue tolerances, with lightness tolerances exhibiting more pronounced effects. Specific textures significantly enhance lightness tolerances when compared to uniform stimuli. This trend is also observable in chroma and hue tolerances for stimuli with specific color centers and texture patterns. Additionally, the research optimized the parametric factors for color-difference formulas (specifically, CIE94, CMC, and CIEDE2000) based on the tolerance dataset. The optimized factors ranged from 0.80 to 1.50, which cast doubts on the widely used 2:1:1 ratio. The analysis suggests that CAM16-UCS is the top performer for calculating color differences in stimuli featuring the examined knitting textures.In a secondary investigation, the study also sought to assess the influence of the dimension and shape of polymeric pellets on their instrumental colorimetric and spectral measurements, with a particular emphasis on measurement repeatability. In the experiments, a range of colorless and translucent granules underwent measurements using the spectrophotometer. Two measurement protocols were applied: bulk measurements, involving filling granules within a 50-mm pathlength glass cuvette, and single-pellet measurements, which measured individual granules against an achromatic backing. For both measurement approaches, the results indicated minimal or inconsistent effects of sample geometries on measurement repeatability. However, the granule varieties with distinct geometric parameters exhibited unique reflectance profiles and significantly varied colorimetric values, suggesting the influential role of granule geometric characteristics in color measurements.
533 $a Electronic reproduction. $b Ann Arbor, Mich. : $c ProQuest, $d 2024
538 $a Mode of access: World Wide Web
650 4 $a Experimental psychology. $3 1180476
650 4 $a Cognitive psychology. $3 556029
655 7 $a Electronic books. $2 local $3 554714
690 $a 0633
690 $a 0623
710 2 $a ProQuest Information and Learning Co. $3 1178819
710 2 $a North Carolina State University. $3 845424
773 0 $t Dissertations Abstracts International $g 85-11B.
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=30984022 $z click for full text (PQDT)