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題名 商標設計之視覺元素分析
Analysis of visual elements for logo design
作者 陳柏銘
Chen, Po Ming
貢獻者 廖文宏
Liao, Wen Hung
陳柏銘
Chen, Po Ming
關鍵詞 商標設計
美學
視覺因子
影像分析
Logo Design
Aesthetics
Visual Factor
Image Analysis
日期 2011
上傳時間 30-Oct-2012 14:01:30 (UTC+8)
摘要 商標是一種藉由圖像或是混和圖像與文字存在的標誌，經由特定的符號或是顏色所組成，利用圖像的組成、配置、形狀、顏色、混合、字體、字體顏色等視覺元素將會帶給人們不同的視覺感受。
過去的研究中，對於視覺元素在商標中扮演的角色偏向質化的探討，通常多利用使用者測試的方法找到設計元素與商標的相關度，較少應用電腦視覺對於圖像量化分析的方法，本研究的目的在於利用各種視覺特徵的計算方式，分析各種商標中視覺元素的組成，包含商標中圖像的複雜度、和諧度、組成重複度等相關量化指標。
藉由大量透過網路上收集的商標進行分析後，可發現商標普遍具有低複雜度、高和諧度、低重複度的設計特性，本論文最後試著以商標獨特性指標代替商標辨識度以驗證本論文設計的分析方法可行性。由於在電腦視覺領域中相關於商標美學的研究並不常見，本論文亦希望能對電腦視覺分析應用在設計或美學的領域進行先導性的研究。
A logo is a mark composed of graph or a combination of text and graph. Typical visual elements in a logo design such as layout, shape, color (foreground and background), composition, and typeface. The graphical mark can exhibit interesting properties by mixing the elements in creative ways.
Most previous researches regarding the role of visual elements in logo design are of qualitative nature. In this thesis, we propose to incorporate visual feature extraction and analysis algorithms commonly utilized in computer vision to compute proper index and investigate key visual elements in logo design, including complexity, harmony and repetition.
After analyzing large amount of logos collected from the internet, we find out that most logos are of low complexity, high balance and exhibit some degree of repetition. We propose a new measure of “distinctiveness” and investigate its relationship with to the aforementioned properties. We hope that the results obtained in thesis serve as a catalyst to motivate further research in applying computer vision methods to the area of aesthetics and design.
參考文獻 [1] C. Chiu-Shui, "Can style be measured?," Design Studies, vol. 21, pp. 277-291, 2000.
[2] T. Jacobsen and L. E. A. Hofel, "Aesthetic Judgments of Novel Graphic Patterns : Analyses of Individual Judgments," Perceptual and Motor Skills, vol. 95, pp. 755-766, 2002.
[3] D. C. L. Ngo and J. G. Byrne, "Aesthetic measures for screen design," in Computer Human Interaction Conference, 1998. Proceedings. 1998 Australasian, 1998, pp. 64-71.
[4] P. A. Russell, The aesthetics of rectangle proportion : Effects of judgment scale and context vol. 113. Champaign, IL, ETATS-UNIS: University of Illinois Press, 2000.
[5] D. D. Psicologia, "Complexity and Aesthetic Preference for Diverse Visual Stimuli," Departament de Psicologia, vol. PhD, pp. 1-439, 2007.
[6] T. Jacobsen, "Beauty and the brain: culture, history and individual differences in aesthetic appreciation," Journal of anatomy, vol. 216, pp. 184-91, Feb 2010.
[7] H. J. Eysenck, "A New Measure of `Good Taste` in Visual Art," Leonardo, vol. 16, pp. 229-231, 1983.
[8] V. Koller, "`Not just a colour`: pink as a gender and sexuality marker in visual communication," Visual Communication, vol. 7, pp. 395-423, 2008.
[9] J. L. Aaker, "Dimensions of Brand Personality," Journal of Marketing Research, vol. 34, pp. 347-356, 1997.
[10] C. Janiszewski and T. Meyvis, "Effects of Brand Logo Complexity, Repetition, and Spacing on Processing Fluency and Judgment," Journal of Consumer Research, vol. 28, pp. 18-32, 2001.
[11] R. van der Lans, J. A. Cote, C. A. Cole, S. M. Leong, A. Smidts, P. W. Henderson, C. Bluemelhuber, P. A. Bottomley, J. R. Doyle, A. Fedorikhin, J. Moorthy, B. Ramaseshan, and B. H. Schmitt, "Cross-National Logo Evaluation Analysis: An Individual-Level Approach," Marketing Science, vol. 28, pp. 968-985, 2009.
[12] R. R. Klink, "Creating Meaningful Brands: The Relationship Between Brand Name and Brand Mark," Marketing Letters, vol. 14, pp. 143-157, 2003.
[13] F. Koschembar, 閱讀平面設計: 教你掌握設計的配方書: 遠流出版事業股份有限公司, 2010.
[14] P. W. Henderson and J. A. Cote, "Guidelines for selecting or modifying logos," Journal of Marketing, vol. 62, pp. 14-30, 1998.
[15] D. G. Lowe, "Object recognition from local scale-invariant features," 1999, pp. 1150-1157 vol. 2.
[16] H. Bay, T. Tuytelaars, and L. Van Gool, "Surf: Speeded up robust features," Computer Vision–ECCV 2006, pp. 404-417, 2006.
[17] A. Wilson and A. Chattertee, "The assessment of preference for balance: introducing a new test. ," Empirical Studies of the Arts, vol. 23, pp. 165-180, 2005.
[18] M. Cardaci, V. Di Gesù, M. Petrou, and M. E. Tabacchi, "A fuzzy approach to the evaluation of image complexity," Fuzzy Sets and Systems, vol. 160, pp. 1474-1484, 2009.
[19] F. Yaghmaee and M. Jamzad, "Introducing a New Method for Estimation Image Complexity According To Calculate Watermark Capacity," pp. 981-984, 2008.
[20] I. Mario, M. Chacon, D. Alma, and S. Corral, "Image complexity measure: a human criterion free approach," in Fuzzy Information Processing Society, 2005. NAFIPS 2005. Annual Meeting of the North American, 2005, pp. 241-246.
[21] J. Rigau, M. Feixas, and M. Sbert, "An Information-Theoretic Framework for Image Complexity," Computational Aesthetics, pp. 177-184, 2005.
[22] R. O. Duda and P. E. Hart, "Use of the Hough transformation to detect lines and curves in pictures," Communications of the ACM, vol. 15, pp. 11-15, 1972.
[23] D. H. Ballard, "Generalizing the Hough transform to detect arbitrary shapes," Pattern recognition, vol. 13, pp. 111-122, 1981.
[24] A. Samal and J. Edwards, "Generalized Hough transform for natural shapes," Pattern Recognition Letters, vol. 18, pp. 473-480, 1997.
[25] N. Bonnet, "An unsupervised generalized Hough transform for natural shapes," Pattern recognition, vol. 35, pp. 1193-1196, 2002.
[26] M. R. Teague, "Image analysis via the general theory of moments*," JOSA, vol. 70, pp. 920-930, 1980.
[27] W. Y. Kim and Y. S. Kim, "A region-based shape descriptor using Zernike moments," Signal Processing: Image Communication, vol. 16, pp. 95-102, 2000.
[28] F. Mokhtarian, "Silhouette-based isolated object recognition through curvature scale space," Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 17, pp. 539-544, 1995.
[29] C. T. Zahn and R. Z. Roskies, "Fourier descriptors for plane closed curves," Computers, IEEE Transactions on, vol. 100, pp. 269-281, 1972.
[30] M. Bober, "MPEG-7 visual shape descriptors," Circuits and Systems for Video Technology, IEEE Transactions on, vol. 11, pp. 716-719, 2001.
[31] D. Marr, Vision: A Computational Investigation into the Human Representation and Processing of Visual Information: Henry Holt & Company, 1983.
[32] D. Zhang and G. Lu, "A comparative study of curvature scale space and Fourier descriptors for shape-based image retrieval," Journal of Visual Communication and Image Representation, vol. 14, pp. 39-57, 2003.
[33] D. Zhang and G. Lu, "Evaluation of MPEG-7 shape descriptors against other shape descriptors," Multimedia Systems, vol. 9, pp. 15-30, 2003.
[34] D. Zhang and G. Lu, "A comparative study on shape retrieval using Fourier descriptors with different shape signatures," 2001, pp. 1-9.
[35] S. Belongie, J. Malik, and J. Puzicha, "Shape context: A new descriptor for shape matching and object recognition," Advances in neural information processing systems, pp. 831-837, 2001.
[36] M. Rusiñol and J. Lladós, "Efficient logo retrieval through hashing shape context descriptors," presented at the Proceedings of the 9th IAPR International Workshop on Document Analysis Systems, Boston, Massachusetts, 2010.
[37] S. Suzuki, "Topological structural analysis of digitized binary images by border following," Computer Vision, Graphics, and Image Processing, vol. 30, pp. 32-46, 1985.
[38] Y. Rubner, L. J. Guibas, and C. Tomasi, "The earth mover`s distance, multi-dimensional scaling, and color-based image retrieval," 1997, pp. 661-668.
[39] D. S. Doermann, E. Rivlin, and I. Weiss, "Logo recognition using geometric invariants," 1993, pp. 894-897.
[40] S. Romberg, L. G. Pueyo, R. Lienhart, and R. van Zwol, "Scalable logo recognition in real-world images," 2011, p. 25.
[41] E. A. El-Kwae and M. R. Kabuka, "A robust framework for content-based retrieval by spatial similarity in image databases," ACM Transactions on Information Systems (TOIS), vol. 17, pp. 174-198, 1999.
[42] B. Li and F. Fonseca, "Tdd: A comprehensive model for qualitative spatial similarity assessment," Spatial Cognition and Computation, vol. 6, pp. 31-62, 2006.
[43] R. H. Van Leuken, M. F. Demirci, V. J. Hodge, J. Austin, and R. C. Veltkamp, "Layout indexing of trademark images," 2007, pp. 525-532.
[44] M. Egenhofer and K. Al-Taha, "Reasoning about gradual changes of topological relationships," Theories and methods of spatio-temporal reasoning in geographic space, pp. 196-219, 1992.
描述 碩士
國立政治大學
資訊科學學系
99753013
100
資料來源 http://thesis.lib.nccu.edu.tw/record/#G0099753013
資料類型 thesis
dc.contributor.advisor 廖文宏zh_TW
dc.contributor.advisor Liao, Wen Hungen_US
dc.contributor.author (Authors) 陳柏銘zh_TW
dc.contributor.author (Authors) Chen, Po Mingen_US
dc.creator (作者) 陳柏銘zh_TW
dc.creator (作者) Chen, Po Mingen_US
dc.date (日期) 2011en_US
dc.date.accessioned 30-Oct-2012 14:01:30 (UTC+8)-
dc.date.available 30-Oct-2012 14:01:30 (UTC+8)-
dc.date.issued (上傳時間) 30-Oct-2012 14:01:30 (UTC+8)-
dc.identifier (Other Identifiers) G0099753013en_US
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/54865-
dc.description (描述) 碩士zh_TW
dc.description (描述) 國立政治大學zh_TW
dc.description (描述) 資訊科學學系zh_TW
dc.description (描述) 99753013zh_TW
dc.description (描述) 100zh_TW
dc.description.abstract (摘要) 商標是一種藉由圖像或是混和圖像與文字存在的標誌，經由特定的符號或是顏色所組成，利用圖像的組成、配置、形狀、顏色、混合、字體、字體顏色等視覺元素將會帶給人們不同的視覺感受。
過去的研究中，對於視覺元素在商標中扮演的角色偏向質化的探討，通常多利用使用者測試的方法找到設計元素與商標的相關度，較少應用電腦視覺對於圖像量化分析的方法，本研究的目的在於利用各種視覺特徵的計算方式，分析各種商標中視覺元素的組成，包含商標中圖像的複雜度、和諧度、組成重複度等相關量化指標。
藉由大量透過網路上收集的商標進行分析後，可發現商標普遍具有低複雜度、高和諧度、低重複度的設計特性，本論文最後試著以商標獨特性指標代替商標辨識度以驗證本論文設計的分析方法可行性。由於在電腦視覺領域中相關於商標美學的研究並不常見，本論文亦希望能對電腦視覺分析應用在設計或美學的領域進行先導性的研究。		zh_TW
dc.description.abstract (摘要) A logo is a mark composed of graph or a combination of text and graph. Typical visual elements in a logo design such as layout, shape, color (foreground and background), composition, and typeface. The graphical mark can exhibit interesting properties by mixing the elements in creative ways.
Most previous researches regarding the role of visual elements in logo design are of qualitative nature. In this thesis, we propose to incorporate visual feature extraction and analysis algorithms commonly utilized in computer vision to compute proper index and investigate key visual elements in logo design, including complexity, harmony and repetition.
After analyzing large amount of logos collected from the internet, we find out that most logos are of low complexity, high balance and exhibit some degree of repetition. We propose a new measure of “distinctiveness” and investigate its relationship with to the aforementioned properties. We hope that the results obtained in thesis serve as a catalyst to motivate further research in applying computer vision methods to the area of aesthetics and design.		en_US
dc.description.tableofcontents 1. 研究背景與目的 1
2. 美學相關研究 6
2.1. Guidelines for Selecting or Modifying Logos 7
2.2. 閱讀平面設計 9
2.3. 小結 10
3. 電腦視覺元素分析相關研究 11
3.1. 影像複雜度 12
3.2. 影像平衡度 13
3.3. 影像形狀描述子 14
3.3.1. Fourier Descriptor 16
3.3.2. Shape Context 18
3.4. 小結 19
4. 研究方法 20
4.1. 商標和諧度 21
4.1.1. 分析方式 21
4.1.2. 參考改進與修正 23
4.2. 商標清晰度 24
4.2.1. 分析方法 24
4.2.2. Entropy: 25
4.2.3. Feature Selection： 25
4.2.4. Threshold 26
4.2.5. Image Partition 26
4.2.6. 複雜度指標 29
4.2.6.1. Feature Entropy 30
4.2.6.2. Partition Entropy 30
4.2.6.3. Area Ratio 30
4.3. 商標元件重複度 31
4.3.1. 分析方法 31
4.3.2. 前處理 32
4.3.3. Fourier Descriptor 33
4.3.4. 輪廓重複度 35
4.4. 小結 36
5. 實驗結果 37
5.1. 商標資料庫與前處理 37
5.2. 商標平衡度 39
5.3. 商標複雜度 43
5.4. 商標元件重複度 48
6. 獨特度與視覺指標 51
6.1. 獨特度 51
6.1.1. 佈局特徵子 51
6.1.2. 前處理 53
6.1.3. 分析方法 53
6.2. 獨特度與商標指標 56
6.2.1. 獨特度與和諧度 57
6.2.2. 獨特度與精細度 58
6.2.3. 獨特度與重複度 59
7. 結論與未來方向 60
8. 參考文獻 61		zh_TW
dc.language.iso en_US-
dc.source.uri (資料來源) http://thesis.lib.nccu.edu.tw/record/#G0099753013en_US
dc.subject (關鍵詞) 商標設計zh_TW
dc.subject (關鍵詞) 美學zh_TW
dc.subject (關鍵詞) 視覺因子zh_TW
dc.subject (關鍵詞) 影像分析zh_TW
dc.subject (關鍵詞) Logo Designen_US
dc.subject (關鍵詞) Aestheticsen_US
dc.subject (關鍵詞) Visual Factoren_US
dc.subject (關鍵詞) Image Analysisen_US
dc.title (題名) 商標設計之視覺元素分析zh_TW
dc.title (題名) Analysis of visual elements for logo designen_US
dc.type (資料類型) thesisen
dc.relation.reference (參考文獻) [1] C. Chiu-Shui, "Can style be measured?," Design Studies, vol. 21, pp. 277-291, 2000.
[2] T. Jacobsen and L. E. A. Hofel, "Aesthetic Judgments of Novel Graphic Patterns : Analyses of Individual Judgments," Perceptual and Motor Skills, vol. 95, pp. 755-766, 2002.
[3] D. C. L. Ngo and J. G. Byrne, "Aesthetic measures for screen design," in Computer Human Interaction Conference, 1998. Proceedings. 1998 Australasian, 1998, pp. 64-71.
[4] P. A. Russell, The aesthetics of rectangle proportion : Effects of judgment scale and context vol. 113. Champaign, IL, ETATS-UNIS: University of Illinois Press, 2000.
[5] D. D. Psicologia, "Complexity and Aesthetic Preference for Diverse Visual Stimuli," Departament de Psicologia, vol. PhD, pp. 1-439, 2007.
[6] T. Jacobsen, "Beauty and the brain: culture, history and individual differences in aesthetic appreciation," Journal of anatomy, vol. 216, pp. 184-91, Feb 2010.
[7] H. J. Eysenck, "A New Measure of `Good Taste` in Visual Art," Leonardo, vol. 16, pp. 229-231, 1983.
[8] V. Koller, "`Not just a colour`: pink as a gender and sexuality marker in visual communication," Visual Communication, vol. 7, pp. 395-423, 2008.
[9] J. L. Aaker, "Dimensions of Brand Personality," Journal of Marketing Research, vol. 34, pp. 347-356, 1997.
[10] C. Janiszewski and T. Meyvis, "Effects of Brand Logo Complexity, Repetition, and Spacing on Processing Fluency and Judgment," Journal of Consumer Research, vol. 28, pp. 18-32, 2001.
[11] R. van der Lans, J. A. Cote, C. A. Cole, S. M. Leong, A. Smidts, P. W. Henderson, C. Bluemelhuber, P. A. Bottomley, J. R. Doyle, A. Fedorikhin, J. Moorthy, B. Ramaseshan, and B. H. Schmitt, "Cross-National Logo Evaluation Analysis: An Individual-Level Approach," Marketing Science, vol. 28, pp. 968-985, 2009.
[12] R. R. Klink, "Creating Meaningful Brands: The Relationship Between Brand Name and Brand Mark," Marketing Letters, vol. 14, pp. 143-157, 2003.
[13] F. Koschembar, 閱讀平面設計: 教你掌握設計的配方書: 遠流出版事業股份有限公司, 2010.
[14] P. W. Henderson and J. A. Cote, "Guidelines for selecting or modifying logos," Journal of Marketing, vol. 62, pp. 14-30, 1998.
[15] D. G. Lowe, "Object recognition from local scale-invariant features," 1999, pp. 1150-1157 vol. 2.
[16] H. Bay, T. Tuytelaars, and L. Van Gool, "Surf: Speeded up robust features," Computer Vision–ECCV 2006, pp. 404-417, 2006.
[17] A. Wilson and A. Chattertee, "The assessment of preference for balance: introducing a new test. ," Empirical Studies of the Arts, vol. 23, pp. 165-180, 2005.
[18] M. Cardaci, V. Di Gesù, M. Petrou, and M. E. Tabacchi, "A fuzzy approach to the evaluation of image complexity," Fuzzy Sets and Systems, vol. 160, pp. 1474-1484, 2009.
[19] F. Yaghmaee and M. Jamzad, "Introducing a New Method for Estimation Image Complexity According To Calculate Watermark Capacity," pp. 981-984, 2008.
[20] I. Mario, M. Chacon, D. Alma, and S. Corral, "Image complexity measure: a human criterion free approach," in Fuzzy Information Processing Society, 2005. NAFIPS 2005. Annual Meeting of the North American, 2005, pp. 241-246.
[21] J. Rigau, M. Feixas, and M. Sbert, "An Information-Theoretic Framework for Image Complexity," Computational Aesthetics, pp. 177-184, 2005.
[22] R. O. Duda and P. E. Hart, "Use of the Hough transformation to detect lines and curves in pictures," Communications of the ACM, vol. 15, pp. 11-15, 1972.
[23] D. H. Ballard, "Generalizing the Hough transform to detect arbitrary shapes," Pattern recognition, vol. 13, pp. 111-122, 1981.
[24] A. Samal and J. Edwards, "Generalized Hough transform for natural shapes," Pattern Recognition Letters, vol. 18, pp. 473-480, 1997.
[25] N. Bonnet, "An unsupervised generalized Hough transform for natural shapes," Pattern recognition, vol. 35, pp. 1193-1196, 2002.
[26] M. R. Teague, "Image analysis via the general theory of moments*," JOSA, vol. 70, pp. 920-930, 1980.
[27] W. Y. Kim and Y. S. Kim, "A region-based shape descriptor using Zernike moments," Signal Processing: Image Communication, vol. 16, pp. 95-102, 2000.
[28] F. Mokhtarian, "Silhouette-based isolated object recognition through curvature scale space," Pattern Analysis and Machine Intelligence, IEEE Transactions on, vol. 17, pp. 539-544, 1995.
[29] C. T. Zahn and R. Z. Roskies, "Fourier descriptors for plane closed curves," Computers, IEEE Transactions on, vol. 100, pp. 269-281, 1972.
[30] M. Bober, "MPEG-7 visual shape descriptors," Circuits and Systems for Video Technology, IEEE Transactions on, vol. 11, pp. 716-719, 2001.
[31] D. Marr, Vision: A Computational Investigation into the Human Representation and Processing of Visual Information: Henry Holt & Company, 1983.
[32] D. Zhang and G. Lu, "A comparative study of curvature scale space and Fourier descriptors for shape-based image retrieval," Journal of Visual Communication and Image Representation, vol. 14, pp. 39-57, 2003.
[33] D. Zhang and G. Lu, "Evaluation of MPEG-7 shape descriptors against other shape descriptors," Multimedia Systems, vol. 9, pp. 15-30, 2003.
[34] D. Zhang and G. Lu, "A comparative study on shape retrieval using Fourier descriptors with different shape signatures," 2001, pp. 1-9.
[35] S. Belongie, J. Malik, and J. Puzicha, "Shape context: A new descriptor for shape matching and object recognition," Advances in neural information processing systems, pp. 831-837, 2001.
[36] M. Rusiñol and J. Lladós, "Efficient logo retrieval through hashing shape context descriptors," presented at the Proceedings of the 9th IAPR International Workshop on Document Analysis Systems, Boston, Massachusetts, 2010.
[37] S. Suzuki, "Topological structural analysis of digitized binary images by border following," Computer Vision, Graphics, and Image Processing, vol. 30, pp. 32-46, 1985.
[38] Y. Rubner, L. J. Guibas, and C. Tomasi, "The earth mover`s distance, multi-dimensional scaling, and color-based image retrieval," 1997, pp. 661-668.
[39] D. S. Doermann, E. Rivlin, and I. Weiss, "Logo recognition using geometric invariants," 1993, pp. 894-897.
[40] S. Romberg, L. G. Pueyo, R. Lienhart, and R. van Zwol, "Scalable logo recognition in real-world images," 2011, p. 25.
[41] E. A. El-Kwae and M. R. Kabuka, "A robust framework for content-based retrieval by spatial similarity in image databases," ACM Transactions on Information Systems (TOIS), vol. 17, pp. 174-198, 1999.
[42] B. Li and F. Fonseca, "Tdd: A comprehensive model for qualitative spatial similarity assessment," Spatial Cognition and Computation, vol. 6, pp. 31-62, 2006.
[43] R. H. Van Leuken, M. F. Demirci, V. J. Hodge, J. Austin, and R. C. Veltkamp, "Layout indexing of trademark images," 2007, pp. 525-532.
[44] M. Egenhofer and K. Al-Taha, "Reasoning about gradual changes of topological relationships," Theories and methods of spatio-temporal reasoning in geographic space, pp. 196-219, 1992.		zh_TW