Logo and Trademark Recognition

Reference work entry


The importance of logos and trademarks in nowadays society is indisputable, variably seen under a positive light as a valuable service for consumers or a negative one as a catalyst of ever-increasing consumerism. This chapter discusses the technical approaches for enabling machines to work with logos, looking into the latest methodologies for logo detection, localization, representation, recognition, retrieval, and spotting in a variety of media. This analysis is presented in the context of three different applications covering the complete depth and breadth of state of the art techniques. These are trademark retrieval systems, logo recognition in document images, and logo detection and removal in images and videos. This chapter, due to the very nature of logos and trademarks, brings together various facets of document image analysis spanning graphical and textual content, while it links document image analysis to other computer vision domains, especially when it comes to the analysis of real-scene videos and images.


Logo recognition Logo removal Logo spotting Trademark registration Trademark retrieval systems 


  1. 1.
    Alajlan N (2007) Retrieval of hand-sketched envelopes in logo images. Lect Notes Comput Sci 4633/2007:436–446CrossRefGoogle Scholar
  2. 2.
    Alajlan N, Kamel MS, Freeman G (2006) Multi-object image retrieval based on shape and topology. Signal Process Image Commun 21(10):904–918CrossRefGoogle Scholar
  3. 3.
    Albiol A, Fulla MJ, Albiol A, Torres L (2004) Detection of TV commercials. In: Proceedings of the international conference on acoustics, speech and signal processing, Montreal, pp 541–544Google Scholar
  4. 4.
    Aldershoff F, Gevers T (2004) Visual tracking and localisation of billboards in streamed soccer matches. SPIE Electron Imaging 5307:408–416Google Scholar
  5. 5.
    Alwis S, Austin J (1999) Trademark image retrieval using multiple features. In: Proceedings of the challenge of image retrieval (CIR-99), BCS electronic workshops in computing, Newcastle-upon-TyneGoogle Scholar
  6. 6.
    Amir A, Lindenbaum M (1998) A generic grouping algorithm and its quantitative analysis. IEEE Trans Pattern Anal Mach Intell 20(2):168–185CrossRefGoogle Scholar
  7. 7.
    Baeza-Yates R, Ribeiro-Neta B (2011) Modern information retrieval: the concepts and technology behind search, 2nd edn. Addison-Wesley, New YorkGoogle Scholar
  8. 8.
    Bagdanov AD, Ballan L, Bertini M, Bimbo AD (2007) Trademark matching and retrieval in sports video databases, in James Ze Wang; Nozha Boujemaa; Alberto Del Bimbo & Jia Li, ed., Multimedia Information Retrieval, ACM, New York, pp 79–86Google Scholar
  9. 9.
    Bay H, Tuytelaars T, Van Gool L (2006) Surf: speeded up robust features. In: ECCV, GrazCrossRefGoogle Scholar
  10. 10.
    Belkin NJ, Kantor P, Fox EA, Shaw JA (1995) Combining evidence of multiple query representations for information retrieval. Inf Process Manag 31(3):431–448CrossRefGoogle Scholar
  11. 11.
    Belongie S, Malik J, Puzicha J (2002) Shape matching and object recognition using shape contexts. IEEE Trans Pattern Anal Mach Intell 24(24):509–522CrossRefGoogle Scholar
  12. 12.
    Bober M, Preteux F, Kim Y-M (2001) MPEG-7 visual shape descriptors. Technical report, Ref: VIL01-D112, Mitsubishi ElectricGoogle Scholar
  13. 13.
    Chan DY-M, King I (1999) Genetic algorithm for weights assignment in dissimilarity for trademark retrieval. In: Huijsmans DP, Smeulders AWM (eds) VISUAL’99, Amsterdam. LNCS 1614, pp 557–565Google Scholar
  14. 14.
    Chang P, Krumm J (1999) Object recognition with color cooccurrence histograms. In: Proceedings of the IEEE conference on computer vision and pattern recognition, Fort Collins, pp 498–504Google Scholar
  15. 15.
    Chen J, Leung MK, Gao Y (2003) Noisy logo recognition using line segment Hausdorff distance. Pattern Recognit 36(4):943–955CrossRefGoogle Scholar
  16. 16.
    Chen J, Wang L, Chen D (2011) Logo recognition: theory and practice. CRC, Boca RatonGoogle Scholar
  17. 17.
    Chou T-C, Cheng S-C (2006) Design and implementation of a semantic image classification and retrieval of organizational memory information systems using analytical hierarchy process. Omega 34:125–134. ElsevierGoogle Scholar
  18. 18.
    Ciocca G, Schettini R (2001) Content-based similarity retrieval of trademarks using relevance feedback. Pattern Recognit 34:1639–1655zbMATHCrossRefGoogle Scholar
  19. 19.
    Cózar JR, Guil N, González-Linares JM, Zapata EL, Izquierdo E (2007) Logotype detection to support semantic-based video annotation. Signal Process Image Commun 22(7–8):669–679CrossRefGoogle Scholar
  20. 20.
    den Hollander RJM, Hanjalic A (2003) Logo recognition in video stills by string matching. In: Proceedings of IEEE international conference on image processing (ICIP), Barcelona, pp 517–520Google Scholar
  21. 21.
    Desolneux A, Moisan L, Morel J-M (2008) From Gestalt theory to image analysis: a probabilistic approach. Springer, New YorkzbMATHCrossRefGoogle Scholar
  22. 22.
    Diligenti M, Gori M, Maggini M, Martinelli E (2001) Adaptive graphical pattern recognition for the classification of company logos. Pattern Recognit 34:2049–2061zbMATHCrossRefGoogle Scholar
  23. 23.
    Doermann D, Rivlin E, Weiss I (1996) Applying algebraic and differential invariants for logo recognition. Mach Vis Appl 9(2):73–86CrossRefGoogle Scholar
  24. 24.
    Duffner S, Garcia C (2006) A neural scheme for robust detection of transparent logos in TV programs. Lecture notes in computer science—II, vol 4132. Springer, Berlin, pp 14–23CrossRefGoogle Scholar
  25. 25.
    Eakins JP, Shields K, Boardman JM (1996) Artisan—a shape retrieval system based on boundary family indexing. In: Sethi IK, Jain RC (eds) Storage and retrieval for image and video databases IV (Proc SPIE 2670). SPIE, Bellingham, pp 17–28CrossRefGoogle Scholar
  26. 26.
    Eakins JP, Boardman JM, Graham ME (1998) Similarity retrieval of trademark images. IEEE Multimed 5(2):53–63CrossRefGoogle Scholar
  27. 27.
    Eakins JP, Riley KJ, Edwards JD (2003) Shape feature matching for trademark image retrieval. In: Bakker EM et al (eds) CIVR 2003, Urbana-Champaign. LNCS 2728, pp 28–38Google Scholar
  28. 28.
    El Badawy O, Kamel M (2002) Shape-based image retrieval applied to trademark images. Int J Image Graph 2(3):375–393. World ScientificGoogle Scholar
  29. 29.
    Esen E, Soysal M, Ates TK, Saracoglu A, Aydin Alatan A (2008) A fast method for animated TV logo detection. In: CBMI, London, pp 236–241, June 2008Google Scholar
  30. 30.
    Fall CJ, Giraud-Carrier C (2005) Searching trademark databases for verbal similarities. World Pat Inf 27:135–143CrossRefGoogle Scholar
  31. 31.
    Fischler M, Bolles R (1981) Random sample consensus: a paradigm for model fitting with applications to image analysis and automated cartography. CACM 24(6):381–395MathSciNetCrossRefGoogle Scholar
  32. 32.
    Gao K, Lin S, Zhang Y, Tang S, Zhang D (2009) Logo detection based on spatial-spectral saliency and partial spatial context. In: Proceedings of the ICME, New York, pp 322–329Google Scholar
  33. 33.
    Gevers T, Stokman H (2004) Robust histogram construction from color invariants for object recognition. Trans Pattern Anal Mach Intell 24:113–118CrossRefGoogle Scholar
  34. 34.
    Giacinto G, Roli F (2005) Instance-based relevance feedback for image retrieval. In: Saul LK, Weiss Y, Bottou L (eds) Advances in neural information processing systems, vol 17. MIT Press, Cambridge, MA, pp 489—496Google Scholar
  35. 35.
    Gori M, Maggini M, Marinai S, Sheng J, Soda G (2003) Edge-Backpropagation for noisy logo recognition. Pattern Recognit 36(1):103–110zbMATHCrossRefGoogle Scholar
  36. 36.
    Grossman DA, Frieder O (2004) Information retrieval: algorithms and heuristics, 2nd edn. Springer, DordrechtzbMATHCrossRefGoogle Scholar
  37. 37.
    Hall D, Pelisson F, Riff O, Crowley JL (2004) Brand identification using Gaussian derivative histograms. Mach Vis Appl 16(1):41–46zbMATHCrossRefGoogle Scholar
  38. 38.
    Hesson A, Androustos D (2008) Logo and trademark detection in images using color wavelet co-occurrence histograms. In: Proceedings of the IEEE international conference on acoustics, speech and signal processing, Las Vegas, pp 1233–1236Google Scholar
  39. 39.
    Hsieh I-S, Fan K-C (2001) Multiple classifiers for color flag and trademark image retrieval. IEEE Trans Image Process 10(6):950zbMATHGoogle Scholar
  40. 40.
    Huet B, Hancock ER (1999) Line pattern retrieval using relational histograms. IEEE Trans Pattern Anal Mach Intell 21(12):1363–1370CrossRefGoogle Scholar
  41. 41.
    Huet B, Hancock ER (2002) Relational object recognition from large structural libraries. Pattern Recognit 35(9):1895–1915zbMATHCrossRefGoogle Scholar
  42. 42.
    Hung M-H, Hsieh C-H, Kuo C-M (2006) Similarity retrieval of shape images based on database classification. J Vis Commun Image Represent 17:970–985CrossRefGoogle Scholar
  43. 43.
    Jain AK, Vailaya A (1998) Shape-based retrieval: a case study with trademark image databases. Pattern Recognit 31(9):1369–1390CrossRefGoogle Scholar
  44. 44.
    Joly A, Buisson O (2009) Logo retrieval with a contrario visual query expansion. In: Proceedings of the 17th ACM international conference on multimedia (MM ’09), Beijing, pp 581–584Google Scholar
  45. 45.
    Kim YS, Kim WY (1998) Content-based trademark retrieval system using a visually salient feature. Image Vis Comput 16:931–939CrossRefGoogle Scholar
  46. 46.
    Kleban J, Xie X, Ma W-Y (2008) Spatial pyramid mining for logo detection in natural scenes. In: Proceedings of the IEEE conference on multimedia expo, Hannover, pp 1077–1080Google Scholar
  47. 47.
    Levenshtein V (1966) Binary codes capable of correcting deletions, insertions, and reversals. Cybern Control Theory 10(8):707–710MathSciNetGoogle Scholar
  48. 48.
    Li Z, Schulte-Austum M, Neschen M (2010) Fast logo detection and recognition in document images. In: Proceedings of the 20th international conference on pattern recognition, Istanbul, pp 2716–2719Google Scholar
  49. 49.
    Logo Dataset (2012) Laboratory for Language and Media Processing (LAMP), University of Maryland.
  50. 50.
    Lowe D (2004) Distinctive image features from scale-invariant keypoints. IJCV 60(2): 91–110CrossRefGoogle Scholar
  51. 51.
    Lowe DG (1985) Perceptual organization and visual recognition. Kluwer Academic, BostonCrossRefGoogle Scholar
  52. 52.
    Luo J, Crandall D (2006) Color object detection using spatial-color joint probability functions. IEEE Trans Image Process 15(6):1443–1453CrossRefGoogle Scholar
  53. 53.
    Manning CD, Raghavan P, Schütze H (2008) Introduction to information retrieval. Cambridge University Press, New YorkzbMATHCrossRefGoogle Scholar
  54. 54.
    Meisinger K, Troeger T, Zeller M, Kaup A (2005) Automatic TV logo removal using statistical based logo detection and frequency selective inpainting. In: Proc. European signal processing conference. Antalya, Turkey, 4–8Google Scholar
  55. 55.
    Meng J, Yuan J, Jiang Y, Narasimhan N, Vasudevan V, Wu Y (2010) Interactive visual object search through mutual information maximization. In: Proceedings of the ACM international conference on multimedia, Firenze, pp 1147–1150Google Scholar
  56. 56.
    Mori G, Belongie S, Malik J (2005) Efficient shape matching using shape contexts. IEEE Trans Pattern Anal Mach Intell 27(11):1832–1837zbMATHCrossRefGoogle Scholar
  57. 57.
    Neumann J, Samet H, Soffer A (2002) Integration of local and global shape analysis for logo classification. Pattern Recognit Lett 23(12):1449–1457zbMATHCrossRefGoogle Scholar
  58. 58.
    Oliva A, Torralba A (2007) The role of context in object recognition. Trends Cogn Sci 11:520–527CrossRefGoogle Scholar
  59. 59.
    Ozay N, Sankur B (2009) Automatic TV logo detection and classification in broadcast videos. In: EUSIPCO 2009, Glasgow, pp 839–843Google Scholar
  60. 60.
    Phan R, Androutsos D (2009) Content-Based retrieval of logo and trademarks in unconstrained color image databases using color edge gradient co-occurrence histograms. Comput Vis Image Underst 114(1):66–84CrossRefGoogle Scholar
  61. 61.
    Pham T (2003) Unconstrained logo detection in document images. Pattern Recognit 36(12):3023–3025zbMATHCrossRefGoogle Scholar
  62. 62.
    Quack T, Ferrari V, Liebe B, Gool LV (2007) Efficient mining of frequent and distinctive feature configurations. In: ICCV, Rio de JaneiroGoogle Scholar
  63. 63.
    Ren M, Eakins JP, Briggs P (2000) Human perception of trademark images: implications for retrieval system design. J Electron Imaging 9(4):564–575CrossRefGoogle Scholar
  64. 64.
    Rocchio JJ Jr (1971) Relevance feedback in information retrieval. The smart system-experiments in automatic document processing. Prentice-Hall, Englewood Cliff, pp 313–323Google Scholar
  65. 65.
    Rusinol M, Llados J (2009) Logo spotting by a bag-of words approach for document categorization. In: ICDAR’09, Barcelona, pp 111–115Google Scholar
  66. 66.
    Rusiñol M, Lladós J (2010) Efficient logo retrieval through hashing shape context descriptors. In: Proceedings of the 9th international workshop on document analysis systems, Boston, pp 215–222Google Scholar
  67. 67.
    Rusiñol M, Nourbakhsh F, Karatzas D, Valveny E, Lladós J (2010) Perceptual image retrieval by adding color information to the shape context descriptor. In: Proceedings of the 20th international conference on pattern recognition, Istanbul. IEEE, pp 1594–1597Google Scholar
  68. 68.
    Rusiñol M, Aldavert D, Karatzas D, Toledo R, Lladós J (2011) Interactive trademark image retrieval by fusing semantic and visual content. In: Advances in information retrieval: 33rd European conference on IR research, Dublin. Lecture notes in computer science, vol 6611, pp 314–325Google Scholar
  69. 69.
    Santos AR, Kim HY (2006) Real-Time opaque and semi-transparent TV logos detection. In: Proceedings of the 5th international information and telecommunication technologies symposium (I2TS), CuiabáGoogle Scholar
  70. 70.
    Sarkar S, Boyer KL (1994) Computing perceptual organization in computer vision. Series in machine perception and artificial intelligence, vol 12. World Scientific, Singapore/River EdgeCrossRefGoogle Scholar
  71. 71.
    Saund E (2003) Finding perceptually closed paths in sketches and drawings. IEEE Trans Pattern Anal Mach Intell 25(4):475–491CrossRefGoogle Scholar
  72. 72.
    Saund E (2011) PPD: platform for perceptual document analysis. PARC TR-2011-1, Nov 2011Google Scholar
  73. 73.
    Schietse J, Eakins JP, Veltkamp RC (2007) Practice and challenges in trademark image retrieval. In: Proceedings of the 6th ACM international conference on image and video retrieval, Amsterdam, pp 518–524Google Scholar
  74. 74.
    Seiden S, Dillencourt M, Irani S, Borrey R, Murphy T (1997) Logo detection in document images. In: Proceedings of the international conference on imaging science, systems, and technology, Las Vegas, Nevada, USA, pp 446–449Google Scholar
  75. 75.
    Sivic J, Zisserman A (2003) Video Google: a text retrieval approach to object matching in videos. In: ICCV, Nice, pp 1470–1477Google Scholar
  76. 76.
    The legacy tobacco document library (LTDL) at UCSF (2006).
  77. 77.
    Tombre K, Lamiroy B (2003) Graphics recognition – from re-engineering to retrieval. In: Proceedings of the seventh international conference on document analysis and recognition, ICDAR03, Edinburgh, pp 148–155Google Scholar
  78. 78.
    Tschumperle D (2006) Fast anisotropic smoothing of multi-valued images using curvature-preserving PDE’s. Int J Comput Vis 68(1):65–82CrossRefGoogle Scholar
  79. 79.
    van de Sande KEA, Gevers T, Snoek CGM (2010) Evaluating color descriptors for object and scene recognition. IEEE Trans Pattern Anal Mach Intell 32(9):1582–1596CrossRefGoogle Scholar
  80. 80.
    Venters CC, Hartley RJ, Cooper MD, Hewitt WT (2001) Query by visual example: assessing the usability of content-based image retrieval system user interfaces. In: Shum H-Y, Liao M, Chang S-F (eds) PCM 2001, Beijing. LNCS 2195, pp 514–521Google Scholar
  81. 81.
    Wang H, Chen Y (2009) Logo detection in document images based on boundary extension of feature rectangles. In ICDAR’09, Barcelona, pp 1335–1339Google Scholar
  82. 82.
    Wang J, Duan L, Li Z, Liu J, Lu H, Jin JS (2006) A robust method for TV logo tracking in video streams. In: Proceedings of the IEEE international conference on multimedia and expo (ICME), Toronto, pp 1041–1044Google Scholar
  83. 83.
    Watve A, Sural S (2008) Soccer video processing for the detection of advertisement billboards. Pattern Recognit Lett (29):994–1006CrossRefGoogle Scholar
  84. 84.
    Wei C-H, Li Y, Chau W-Y, Li C-T (2009) Trademark image retrieval using synthetic features for describing global shape and interior structure. Pattern Recognit 42:386–394zbMATHCrossRefGoogle Scholar
  85. 85.
    Wertheimer M (1938) Untersuchungen zur Lehre der Gestalt, II. Psychologische Forschung, vol 4, pp 301–350, 1923. Translation published as Laws of organization in perceptual forms. In: Ellis W (ed) A source book of Gestalt psychology, Routledge and Kegan Paul, London, pp 71–88Google Scholar
  86. 86.
    Witkin AP, Tenenbaum JM (1982) On the role of structure in human and machine vision. In: Beck J, Hope B, Rosenfeld A (eds) Human and machine vision. Academic Press, New York, pp 481–543Google Scholar
  87. 87.
    World Intellectual Property Organization (2007) International classification of the figurative elements of Marks (Vienna classification), 6th edn. WIPO publication No. 502E/6, Geneva, Academic Press, New YorkGoogle Scholar
  88. 88.
    Wu JK, Lam CP, Mehtre BM, Gao YJ, Desai Narasimhalu A (1996) Content based retrieval for trademark registration. Multimed Tools Appl 3(3):245–267CrossRefGoogle Scholar
  89. 89.
    Yan WQ, Wang J, Kankanhalli MS (2005) Automatic video logo detection and removal. Multimed Syst 10(5):379–391CrossRefGoogle Scholar
  90. 90.
    Zhang D, Lu G (2004) Review of shape representation and description techniques. Pattern Recognit 37:1–19CrossRefGoogle Scholar
  91. 91.
    Zhu G, Doermann D (2007) Automatic document logo detection. In: Proceedings of the international conference on document analysis and recognition, Curitiba, pp 864–868Google Scholar

Copyright information

© Springer-Verlag London 2014

Authors and Affiliations

  1. 1.Department of Surveying EngineeringTechnological Educational Institution of AthensAigaleo, AthensGreece
  2. 2.Computer Vision CenterUniversitat Autònoma de BarcelonaBellaterraSpain

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