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Using Color Management to Automate the Color Reproduction of 3-D Images Procured Via a Digital Camera/3-D Scanner Kristl Honda

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Using Color Management to Automate the Color Reproduction of 3-D Images Procured Via a Digital Camera/3-D Scanner Kristl Honda Rochester Institute of Technology RIT Scholar Works Theses Thesis/Dissertation Collections 5-1-1995 Using color management to automate the color reproduction of 3-D images procured via a digital camera/3-D scanner Kristl Honda Follow this and additional works at: http://scholarworks.rit.edu/theses Recommended Citation Honda, Kristl, "Using color management to automate the color reproduction of 3-D images procured via a digital camera/3-D scanner" (1995). Thesis. Rochester Institute of Technology. Accessed from This Thesis is brought to you for free and open access by the Thesis/Dissertation Collections at RIT Scholar Works. It has been accepted for inclusion in Theses by an authorized administrator of RIT Scholar Works. For more information, please contact [email protected]. Using color management to automate the color reproduction of 3-d images procured via a digital camera/3-d scanner. by Kristl J. Honda A thesis project submitted in partial fulfillment of the requirements for the degree of Master of Science in the School of Printing Management and Sciences in the College of Imaging Arts and Sciences of the Rochester Institute of Technology May 1995 Thesis Advisor: Professor Frank Cost School of Printing Management and Sciences Rochester Institute of Technology Rochester, NY CERTIFICATE OF ApPROVAL MASTER'S THESIS This is to certify that the Master's Thesis of Krist! J. Honda with a major in Graphic Arts/Electronic Publishing has been approved by the Thesis Committee as satisfactory for the thesis requirement for the Master of Science degree at the convocation of May 1995 Thesis Committee: Frank Cost Thesis Advisor Marie Freckleton Graduate Program Coordinator C. Harold Goffin Director or Designate USING COLOR MANAGEMENT TO AUTOMATE THE COLOR REPRODUCTION OF 3-D IMAGES PROCURED VIA A DIGITAL CAMERA/3-D SCANNER. I, Kristl J. Honda, hereby grant permission to the Wallace Memorial Library of RI.T. to reproduce my thesis in whole or in part. Any reproduction will not be for commercial use or profit. Krist! J. Honda Date 11 Dedication To the Honda family (Joyce, Bob, Daryl, and Wesley) in Sacramento, California for their unconditional support. To the Harper Street family (Alan, Justin, Tricia, Mike, Amber, and Russ) for their friendship, feasts, and fun. in Acknowledgements To the many people who have offered their assistance and provided guidance through my graduate work at R.I.T., I am grateful for your time and effort. To Professor Frank Cost, my thesis advisor, for his inspiration, brainpower, enthusiasm, and sense of humor during this process. To Marie Freckleton, my graduate program coordinator, for her support, patience, and understanding smile during my stay at R.I.T. To Professors Bob Chung and Joe Noga, for teaching me the fundamentals of color print reproduction, and applications of desktop prepress technologies. To Li-Yi Ma, for sharing his knowledge and providing assistance. To David Tontarski and Bill Birkett for providing me with valuable work experi ence opportunities. To the Technical and Education Center for allowing me to use their equipment and facilities. IV Table of Contents Page List of Tables vii List of Figures viii Abstract ix Chapter I Introduction 1 The Statement of Problem 1 Background and Significance 2 Reasons for Interest 4 Endnotes for Chapter I 5 Chapter n - Background Theory 6 The Open Desktop Color System 6 Desktop Color Separation 8 Color Reproduction Requirements 8 Digital Color Principles 11 Color Vision and Perception 11 RGB-Light Mixing Systems 12 Color Spaces 14 Color Gamuts 16 Endnotes for Chapter II 17 Chapter m - Literature Review 19 Color Management Systems 19 CMS Methodology 20 CMS Technology 21 Color Standards for CMS 22 Kodak's PCS100 Color Management System 23 Calibration and Characterization 24 Color Conversion 25 Digital Photography 25 Digital vs. Analog 26 Digital Camera Basics 26 Digital Imaging Trends 28 Systems' Leaf Lumina Digital Camera 29 Endnotes for Chapter III 31 v Chapter IV - Statement of Project Goals 33 Hypothesis 33 Chapter V - Methodology 34 Experimental Design 34 Digital Image Capture 34 Device Characterization 35 Image Color Conversion 35 Subjective Evaluation 37 Objective Evaluation 38 Equipment and Materials Used 39 Endnotes for Chapter V 41 Chapter VI - The Results 42 Subjective Evaluation 42 Results of Visual Assessments 42 Analysis of the Results 42 Objective Evaluation 46 Results of Colorimetric Measurements 46 Analysis of the Results 46 Chapter VII Summary and Conclusions 49 Summary 49 Hypothesis 50 Conclusions 50 Implications 51 Suggestions for Further Research 52 Bibliography 53 Appendices 57 Appendix A: Workflows with and without CMS 58 Appendix B: Special Effects Precision Transforms 60 Appendix C: Memo to the Judges 62 Appendix D: Instructions to the Judges 64 Appendix E: Script for Color Vision Test 66 Appendix F: Script for Administering the Evaluations 68 Appendix G: Master Response Sheets 70 Appendix H: Equations for Color-Difference Calculations 74 Appendix I: CLE Measurements and Calculations 76 Appendix J: AE Charts for MacBeth Color Patches and Objects 78 AL*AC*AH* Appendix K: Charts for MacBeth Color Patches and Objects . 81 vi List of Tables Page Table 1: Printing dot sizes for gray balance 10 Table 2: Analysis of subjective evaluation for tone reproduction 43 Table 3: Analysis of subjective evaluation for gray balance 43 Table 4: Analysis of subjective evaluation for pleasing color 44 Table 5: Analysis of average scores for subjective evaluation 45 Table 6: Analysis of average scores for tone and color only 45 Table 7: Color difference interpretation 47 Table 8: Summary of means and standard deviations 47 vn List of Figures Page Figure 1: Proof #1 (no input, no effect, output) 84 Figure 2: Proof #2 (input, no effect, output) 86 Figure 3: Proof #3 (input, effectOl, output; 88 Figure 4: Proof #4 (input, effect02, output 90 Figure 5: Proof #5 (input, effect03, output 92 Figure 6: Proof #6 (input, effect04, output; 94 Figure 7: Proof #7 (input, effect05, output; 96 Figure 8: Proof #8 (input, effect06, output; 98 Figure 9: Proof #9 (input, effect07, output; 100 Figure 10: Proof #10 (input, snappy neutrals effect, output) 102 vm Abstract The use of digital photography is migrating from the major applications in pho tojournalism to professional studio photography. Traditional service bureaus such as professional photo labs and prepress trade shops are adding digital imaging services to their film-based services. Also, businesses such as advertising agencies and publishers, who traditionally outsource work to service bureaus, are bringing digital imaging services in-house. State of the art imaging technology empowers users with new tools, but does not guarantee that the task of generating accept able image reproductions will be easier. The basic problem in the desktop color prepress environment is that each com ponent in this open system handles color differently. Miscommunication between devices results in user frustration with an unpredictable, inconsistent, and inac curate color system. The solution to this problem is to assess one's workflow and adopt a color management system (CMS). The purpose of CMSs is to help users maintain color integrity throughout their desktop system and to automate the color separation process. This thesis project investigated the possibility of applying a comprehensive CMS to automate the color reproduction of 3-D images procured with a digital camera. Automatic exposure by Leaf System's Lumina digital camera and automatic adjustments for tone reproduction, gray balance, and color correction by Kodak's PCS100 CMS were employed. The experimental design began with the calibration of each component in the imaging chain. Next, a three-dimensional test scene of objects displaying tone and color variety was digitized by the Lumina camera under specific studio lighting conditions. And, under the exact studio conditions, a Kodak Q-60 test target was digitized; this image file was used to characterize a device profile for the Lumina digital camera. The digitized 3-D test scene file was sent through a color-managed workflow for automatic color reproduction. IX The automated, color-managed reproduction process was as follows: 1) select monitor, input, effect, and output profiles in the PCS100 Color Manager 2) acquire image via Photoshop on a Macintosh 3) image color conversion with Kodak's PCS100 plug-ins by applying custom input profile, output simulation profile, and 3M Matchprint output profile 4) film output via Agfa Selectset 5000, and 5) 3M Matchprint color proofing to SWOP (Specifications for Web Offset Printing). Subjective evaluation was based on the single stimulus method. Visual assess ments were performed by twenty color-tested judges with experience in printing or photography. A set of ten color proofs of identical image were individually evaluated for acceptability. The criteria for acceptable color reproduction includ ed tone reproduction, gray balance, and color correction. Proofs that received high average scores (>80%) were determined acceptable. Analysis of the results determined that with proper calibration and CMS color conversion technology, one can deliver acceptable tone reproduction and pleasing color. Gray balance was determined unacceptable for all proofs based solely on a perceived yellow ish-green cast in the MacBeth ColorChecker's three-quarter tone patch. Excluding the gray balance factor, four proofs were determined acceptable for tone and color reproduction. Objective evaluation was made to further assess the color accuracy from original to acceptable proof, and to correlate colorimetric differences with the visual CIEL*a*b* assessments. Quantitative assessment was based on colorimetric mea surements and calculated color differences (AE, AL*, AC*, AHab*) of MacBeth color patches and 3-D objects. Objects in the original scene and corresponding image areas in the proofs were measured in order to study variations in hue, light ness, and saturation. Analysis of the results demonstrated that overall, the images in the proof were lighter, less saturated, and had small hue shifts compared to the original.
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