跳到主要內容

臺灣博碩士論文加值系統

(3.237.6.124) 您好!臺灣時間:2021/07/24 04:35
字體大小: 字級放大   字級縮小   預設字形  
回查詢結果 :::

詳目顯示

: 
twitterline
研究生:鄭存閔
研究生(外文):Chun-MinCheng
論文名稱:平面視覺質感輔助色彩知覺障礙者之辨識
論文名稱(外文):The Composition of Visual Texture Design on Surface for Color Vision Deficiency
指導教授:吳豐光吳豐光引用關係
指導教授(外文):Fong-Gong Wu
學位類別:碩士
校院名稱:國立成功大學
系所名稱:工業設計學系碩博士班
學門:設計學門
學類:產品設計學類
論文種類:學術論文
論文出版年:2012
畢業學年度:100
語文別:英文
論文頁數:72
中文關鍵詞:色彩視覺色彩知覺障礙質感辨識心理物理學色彩閾值
外文關鍵詞:color visioncolor vision deficiencytexture compositionpsychophysicscolor threshold
相關次數:
  • 被引用被引用:1
  • 點閱點閱:284
  • 評分評分:
  • 下載下載:31
  • 收藏至我的研究室書目清單書目收藏:0
  色彩知覺障礙者(color vision deficiency, 簡稱CVD)對於某些特定色彩容易混淆甚至喪失色覺,全球約有8%男性及0.4~0.5%女性患有不同程度及類型的色彩知覺障礙。但色彩為生活中資訊傳達的重要媒介,因此,若無法正確辨識色彩可能為生活帶來諸多不便甚至構成威脅。
  本實驗目的為利用質感具有區分不同表面的特性,又能完整傳達色彩圖示內容的優勢,以色彩視覺原理及視覺理論為發展基礎,提出質感構成的原則,以輔助色彩知覺障礙者之辨識,並兼顧一般視覺者的觀感。
  本研究採用心理物理學法,以紅色RGB (255, 0, 0)為質感背景,並先將質感解構後依據理論進行操作型定義。實驗首先藉由調整法測定色彩閾值,比較一般色覺者和色彩知覺障礙者對於特定色彩配色的辨識力。再利用定值刺激法,請受測者進行質感構成的辨識任務。最後,以一般色覺者的主觀評量從中評選出不影響觀看的質感構成。
  研究結果顯示,於紅色背景上的質感單元色彩若設定為RGB (234, 0, 21)、大小2.5'、間距2.5',可快速被色彩知覺障礙者察覺,且不影響一般色覺者的觀感;而單元大小1.67'、間距 5'則可應用於無須快速閱讀的資訊。設計師可依據載體觀看距離及用途,將此參數進行倍數調整,未來可進行不同載體材質特性的研究,歸納出一套針對各種情境的質感設計法則,以供設計師檢索利用。

  Color serves as a nonlinguistic code that gives us instant information about the world around us, but there are 8% of males and 0.4~0.5% of females suffer from different levels of color vision deficiency (CVD). It may cause much inconvenience as well as serious security problems in the daily lives.
  Based on color vision and visual perception theories, this study aimed to create a set of texture composition principles that not only supports a person with CVD to distinguish colors, but also maintains the visibility and aesthetic of the target.
  The study defined the texture background as redRGB (255, 0, 0). After the operational definition, a focus on the independent variable of texture color, elements size, and distance was possible.The preliminary experiment is color threshold measurement through the adjustment method of psychophysics; second, the constant stimuli method was employed to measure the visible texture compositions by CVDs and normal color vision (NCV) people; and third, NCVs were asked to subjectively evaluate the influence level by Likert scale so that the best texture composition principle could be created from the results.
  Depending on the purpose and position of the application, designers can decide which compositions benefit viewers. For being detected immediately by CVDs, the proper parameters on a red background are the texture elements with RGB (234, 0, 21) color, size 2.5', and distance 2.5'. For website designs or commercial advertisements, designers can choose a smaller size 1.67' and distance 5', so CVDs can easily read the information without a lack of aesthetics for NCVs.

CONTENTS
摘要 II
ABSTRACT III
ACKNOWLEDGEMENT IV
LIST OF TABLES VII
LIST OF FIGURES VIII
APPENDIX IX
CHAPTER 1INTRODUCTION 1
1.1BACKGROUND AND MOTIVATION 1
1.2OBJECTIVES 5
1.3LIMITATION 7
1.4ORGANIZATION 8
CHAPTER 2LITERATURE REVIEW 9
2.1HUMAN COLOR VISION 9
2.2COLOR VISION DEFICIENCY 11
2.2.1Type of CVD 12
2.2.2Tests for CVD 16
2.2.3Related researches and tools of supporting CVD 17
2.2.4Summary 20
2.3FEATURE- INTEGRATION THEORY 21
2.4TEXTURE 22
2.5VISUAL PERCEPTION THEORIES 23
2.5.1Visual acuity 23
2.5.2Spatial frequency 24
2.5.3Summary 25
CHAPTER 3METHODS 26
3.1PSYCHOPHYSICS 28
3.2OPERATIONAL DEFINITION OF TEXTURE FACTORS 29
3.3COLOR THRESHOLD MEASUREMENT 31
3.4DISCRIMINATION TEST OF TEXTURE COMPOSITION 37
3.5EVALUATION OF TEXTURE COMPOSITIONS FOR NCV 41
CHAPTER 4RESULTS 45
4.1THE RESULTS OF TEXTURE DISCRIMINATION 45
4.1.1The texture discrimination rate of CVDs and NCVs 45
4.1.2Response time of texture composition 46
4.1.3The interaction effect of color vision, size and distance 49
4.2THE RESULTS OF TEXTURE EVALUATION FOR NCV 52
4.2.1Subjective evaluation 52
4.2.2Cluster analysis 54
CHAPTER 5DISCUSSION AND CONCLUSIONS 57
5.1DISCUSSION 57
5.1.1Color threshold measurement 57
5.1.2Discrimination test of the texture composition 58
5.1.3Texture evaluation for NCV 59
5.2CONCLUSIONS 63
REFERENCES 64
CHINESE REFERENCES 68


LIST OF TABLES
Table 1.1 Contents of daily life tasks 2
Table 1.2 Contents of occupation 3
Table 1.3 Analysis of CVD impact level on three parts of everyday tasks 4
Table 2.1 Classification of CVD types 15
Table 2.2 Related Researches and Tools to Support CVD 20
Table 3.1 Texture operational definition 30
Table 3.2 Sequence of tasks 33
Table 3.3 Independent-Sample t-test about the color threshold of CVD and NCV 35
Table 3.4 Conversion of Visual Acuity 37
Table 3.5 Stimuli factors 38
Table 3.6 16 types of texture composition 38
Table 4.1 Descriptive Statistics for discrimination rate 45
Table 4.2 Descriptive Statistics for response time of CVDs 47
Table 4.3 Descriptive Statistics for response time of NCVs 47
Table 4.4 Results of Repeated Measure ANOVA for 3 factors 49
Table 4.5 CVDs’ RT result for Repeated Measure ANOVA in 2 factors 50
Table 4.6 Simple main effect of RT 51
Table 4.7 Descriptive Statistics in subjective evaluation of 16 textures 52
Table 4.8 Influences of two variables in three clusters 55
Table 4.9 Proper texture compositions for supporting CVD 56
Table 4.10 Repeated Measure ANOVA of cluster2 56

LIST OF FIGURES
Figure 1.1 Research framework 8
Figure 2.1 Minimal separable visual angle 24
Figure 3.1 Experiment framework 27
Figure 3.2 Texture segregation 29
Figure 3.3 Evaluation frame of program 33
Figure 3.4 Evaluation process of color threshold measurement. 34
Figure 3.5 Experimental process 34
Figure 3.6 Results of threshold measurement 35
Figure 3.7 Histogram of color threshold 36
Figure 3.8 Interface of E-Prime software 40
Figure 3.9 Sequence in a trial 40
Figure 3.10 Evaluation process of discrimination test 41
Figure 3.11 Arrangement for experimental area 42
Figure 3.12 Experiment program frame. 43
Figure 3.13 Evaluation process of 16 textures 43
Figure 3.14 Experimental process 44
Figure 4.1 Bar chart of discrimination rates for CVDs and NCVs 46
Figure 4.2 Profile plot of 16 Textures 48
Figure 4.3 Simple Scatter Plot of 16 textures 53
Figure 4.4 Dendrogram 54
Figure 4.5 Simple Scatter Plot of 16 textures with the results of cluster analysis 55
Figure 5.1 Simulation of texture applied in website information 61
Figure 5.2 Simulation of texture applied in computer game 62
APPENDIX
Appendix 1 Questionnaire of CVD in Everyday Tasks 69
Appendix 2 Color Threshold Measurement 71
Appendix 3 Evaluation of Texture Compositions 72

REFERENCES
Birch, J. (1993). Diagnosis of defective colour vision. Oxford University Press, New York.
Blostein, D. & Ahuja, N. (1989). Shape from texture: Integrating texture-element extraction and surface estimation. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 11(12),1233-1251.
Bruno, T. J.& Svoronos, P. D. N. (2006). CRC handbook of fundamental spectroscopic correlation charts.CRC.
Buckley, D., Frisby, J. P.& Blake, A. (1996). Does the human visual system implement an ideal observer theory of slant from texture? Vision Research, 36(8), 1163-1176.
Chen, Y. C.& Liao, T. S. (2011). Hardware digital color enhancement for color vision deficiencies. ETRI Journal, 33(1).
Childress, D. D. C. (2008). The power of color: Shades of meaning.ProQuest LLC, USA.
CUDO. (2006). Color universaldesign handbook.CUDO, Japan
Dain, S. J. (2004). Clinical colour vision tests. Clinical and Experimental Optometry,87(4‐5),276-293.
Furbee, N. L., Maynard, K., Smith, J. J., Benfer Jr, R. A., Quick, S.& Ross, L. (1996). The emergence of color cognition from color perception. Journal of Linguistic Anthropology, 6(2), 223-240.
Gündogan, N. Ü., Durmazlar, N., Gümüs, K., Özdemir, P. G., Altintas, A. G. Ü. L., Durur, I.& Acaroglu, G. (2005). Projected color slides as a method for mass screening test for color vision deficiency (a preliminary study). International journal of neuroscience, 115(8), 1105-1117.
Galun, M., Sharon, E., Basri, R.& Brandt, A. (2003). Texture segmentation by multiscale aggregation of filter responses and shape elements.Proceedings of the Ninth IEEE International Conference on Computer Vision.
Goldstein, E. B. (2010). Sensation and perception, 8th ed.Wadsworth Cengage Learning, Australia.
Gregory, R. L.(1997). Eye and brain: The psychology of seeing.Princeton university press.
Grove, L. K. (1991). Document design for the visually impaired.The ExpandingEnvironmentof TechnicalCommunication.
Hugh J. Foley, Margaret W. Matlin. (2010). Sensation and perception, 5th ed. Allyn & Bacon. Boston, 204-205.
Jacobs, D. M.& Díaz, A. (2010). Judgements of time to contact are affected by rate of appearance of visible texture. The Quarterly Journal of Experimental Psychology, 63(6),1041-1048.
Jefferson, L.& Harvey, R. (2006). Accommodating color blind computer users. ProceedingAssets '06 Proceedings of the 8th international ACM SIGACCESS conference on Computers and accessibility, 40 - 47.
Jefferson, L.& Harvey, R. (2007). An interface to support color blind computer users.CHI 2007 Proceedings-Color/Blind,USA.
Jeong, J. Y., Kim, H. J., Kim, Y. H., Wang, T. S.& Ko, S. J. (2012). Enhanced Re-coloring Method with an Information Preserving Property for Color-Blind Person. Paper presented at the 2012 IEEE International Conference on Consumer Electronics (ICCE).
Kim, Y. K., Kim, K. W.& Yang, X. (2007). Real time traffic light recognition system for color vision deficiencies, Proceedings of the 2007 IEEEInternational Conference on Mechatronics and Automation, China
Linhares, J. M. M., Felgueiras, P. E. R., Pinto, P. D.& Nascimento, S. (2010). Colour rendering of indoor lighting with CIE illuminants and white LEDs for normal and colour deficient observers. Ophthalmic and Physiological Optics, 30(5),618-625.
McDowell, J. (2008). Design of a color sensing system to aid the color blind. Potentials, IEEE, 27(4), 34-39.
Motoyoshi, I. (2011). Attentional modulation of temporal contrast sensitivity in human vision. PloS one, 6(4), e19303.
Mullen, K. T. (1985). The contrast sensitivity of human colour vision to red-green and blue-yellow chromatic gratings. The Journal of Physiology, 359(1), 381.
Muttaqin, G. F.& Suwandi, I. S. (2011). Simulation system of color blind glasses by image processing. Electrical Engineering and Informatics (ICEEI).
Neitz, M.& Neitz, J. (2011). Molecular genetics of color visionand color vision defects. Mechanisms of Ophthalmic Disease.
O'Hare, L.& Hibbard, P. B. (2011). Spatial frequency and visual discomfort. Vision Research.
Ochiai, T. (2008). LED road traffic signal light.EP Patent 1,973,088.
Ofen, N., Moran, A.& Sagi, D. (2007). Effects of trial repetition in texture discrimination. Vision Research, 47(8), 1094-1102.
Okabe, M., & Ito, K. (2008). Color Universal Design (CUD)-How to make figures and presentations that are friendly to Colorblind people. Depository for Drosophila Researchers.
Poret, S., Dony, R.& Gregori, S. (2009). Image processing for colour blindness correction, TIC-STH 2009 IEEE
Prinzmetal, W. (1981). Principles of feature integration in visual perception. Attention, Perception, & Psychophysics, 30(4), 330-340.
Steven, H. S. (2010). Visual perception: aclinical orientation. McGraw-Hill Medical, New York, 6-9.
Sacks, O. W. (1997). The island of the colorblind;and,Cycad island,Vintage Books, New York.
Sharpe, L. T., de Luca, E., Hansen, T., Jägle, H. & Gegenfurtner, K. R. (2006). Advantages and disadvantages of human dichromacy. Journal of vision, 6(3).
Simunovic, M. (2009). Colour vision deficiency. Eye, 24(5),747-755.
Smith, V. C. & Pokorny, J. (2003). Color matching and color discrimination. The science of color, 2, 103-148.
Stward, J. M. & Cole, B. L. (1989). What do color vision defectives say about everyday tasks? Optometry & Vision Science, 66(5),288.
Szczesniak, A. S. (2002). Texture is a sensory property. Food Quality and Preference, 13(4), 215-225.
Treisman, A. M., & Gelade, G. (1980). A feature-integration theory of attention. Cognitive psychology, 12(1), 97-136.
Valberg, A. (2005). Light vision color.John Wiley & Sons, Hoboken, NJ.
Wachtler, T., Dohrmann, U. & Hertel, R. (2004). Modeling color percepts of dichromats. Vision Research, 44(24), 2843-2855.


Chinese References
Oyama, T. (1998)。色彩心理學-追隨牛頓和歌德的腳步。牧村圖書出版。台北。
李江山、孫慶文、陳一平、陳建中、黃淑麗、黃榮村、葉素、襲充文& Sakurai, S. (1999)。視覺與認知─視覺知覺與視覺運動系統。遠流出版公司。台北。128-130。
林智祥 (2009)。色彩之前進後退與膨脹收縮感之定量測量;碩士論文。國立交通大學應用藝術研究所。
林昆範(2005)。色彩原論。全華圖書公司。台北。
孟慶茂&常建華 (2000)。心理實驗學。心理出版社股份有限公司。台北。 82-97。
高淑玲 (2004)。色彩認知和配色感覺之研究─以改變配色形狀和面積比對色彩意象影響為例。國立雲林科技大學視覺傳達研究所。
陳一平 (2004)。應用色彩學研究;行政院國家科學委員會專題研究計畫。國立交通大學應用藝術研究所。
陳一平 (2011)。視覺心理學。雙葉書廊。台北。
郭明堂 (2003)。危險標誌用語及顏色之認知研究。嘉南藥理科技大學工業安全衛生系。
黃鈺斯 (2010)。針對色彩知覺障礙者設計之新式三原色辨識系統;碩博士論文。成功大學工業設計學系。
曾祥炎&陳軍 (2009)。E-Prime 實驗設計技術。暨南大學出版社。
葉素玲&劉慧珠 (1997)。人類的型態視覺。科學月刊。

連結至畢業學校之論文網頁點我開啟連結
註: 此連結為研究生畢業學校所提供,不一定有電子全文可供下載,若連結有誤,請點選上方之〝勘誤回報〞功能,我們會盡快修正,謝謝!
QRCODE
 
 
 
 
 
                                                                                                                                                                                                                                                                                                                                                                                                               
第一頁 上一頁 下一頁 最後一頁 top