Human perception of trademark images: Implications for retrieval system design

A crucial aspect of shape similarity estimation is the identification of perceptually significant image elements. In order to understand more about the process of human segmentation of abstract images, a sample of 63 trademark images was shown to several groups of students in two experiments. Students were first presented with printed versions of a number of abstract trademark images, and invited to sketch their preferred segmentation of each image. A second group of students was then shown each image, plus its set of alternative segmentations, and invited to rank each alternative in order of preference. Our results suggest that most participants used a relatively small number of segmentation strategies, reflecting well-known psychological principles. Agreement between human image segmentations and those generated by the ARTISAN trademark retrieval system was quite limited; the most common causes of discrepancy were failure to handle texture and incorrect grouping of components into regions. Ways of improving ARTISAN'S ability to model human segmentation behavior are discussed.

[1]  Max Wertheimer,et al.  Untersuchungen zur Lehre von der Gestalt , .

[2]  R. Manmatha,et al.  Multi-modal Retrieval of Trademark Images Using Global Similarity TITLE2: , 1999 .

[3]  Shu-Yuan Chen,et al.  Trademark shape recognition using closed contours , 1997, Pattern Recognit. Lett..

[4]  S. Grossberg Cortical dynamics of three-dimensional figure-ground perception of two-dimensional pictures. , 1997 .

[5]  Whoi-Yul Kim,et al.  Development of Content‐Based Trademark Retrieval System on the World Wide Web , 1999 .

[6]  Simone Santini,et al.  Similarity Measures , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Mary C. Dyson,et al.  Retrieving Symbols from a Database by their Graphic Characteristics: Are Users Consistent? , 1997, J. Vis. Lang. Comput..

[8]  Alex Pentland,et al.  Photobook: tools for content-based manipulation of image databases , 1994, Electronic Imaging.

[9]  Anil K. Jain,et al.  Object Matching Using Deformable Templates , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[10]  E Goldmeier,et al.  Similarity in visually perceived forms. , 1972, Psychological issues.

[11]  Ralph Roskies,et al.  Fourier Descriptors for Plane Closed Curves , 1972, IEEE Transactions on Computers.

[12]  Toshikazu Kato,et al.  Database architecture for content-based image retrieval , 1992, Electronic Imaging.

[13]  S. Grossberg Cortical dynamics of three-dimensional figure-ground perception of two-dimensional pictures. , 1997, Psychological review.

[14]  Greet Frederix,et al.  Content-based image retrieval as a tool for image understanding , 1999, Optics East.

[15]  Jim Austin,et al.  Trademark image retrieval using multiple features , 1999 .

[16]  Jim Austin,et al.  A Novel Architecture for Trademark Image Retrieval Systems , 1998 .

[17]  I. Biederman Recognition-by-components: a theory of human image understanding. , 1987, Psychological review.

[18]  Anil K. Jain,et al.  Shape-Based Retrieval: A Case Study With Trademark Image Databases , 1998, Pattern Recognit..

[19]  Edward H. Adelson,et al.  The Laplacian Pyramid as a Compact Image Code , 1983, IEEE Trans. Commun..

[20]  John P. Eakins,et al.  Similarity Retrieval of Trademark Images , 1998, IEEE Multim..

[21]  David Mumford,et al.  Mathematical theories of shape: do they model perception? , 1991, Optics & Photonics.

[22]  John P. Eakins,et al.  ARTISAN: a shape retrieval system based on boundary family indexing , 1996, Electronic Imaging.

[23]  Rajiv Mehrotra,et al.  Similar-Shape Retrieval in Shape Data Management , 1995, Computer.

[24]  M. Wertheimer Untersuchungen zur Lehre von der Gestalt. II , 1923 .

[25]  W. D. Ross,et al.  A Neural Theory of Attentive Visual Search : Interactions of Boundary , Surface , Spatial , and Object Representations By : Stephen Grossberg , 2004 .

[26]  F. Attneave Some informational aspects of visual perception. , 1954, Psychological review.

[27]  Martin A. Fischler,et al.  Locating Perceptually Salient Points on Planar Curves , 1994, IEEE Trans. Pattern Anal. Mach. Intell..

[28]  Thierry Pun,et al.  A Comparison of Human and Machine Assessments of Image Similarity for the Organization of Image Databases Scandinavian Conference on Image Analysis June 9{11, 1997, Lappeenranta, Finland , 1997 .

[29]  Benjamin B. Kimia,et al.  Shock-based approach for indexing of image databases using shape , 1997, Other Conferences.

[30]  Kim L. Boyer,et al.  A Computational Structure for Preattentive Perceptual Organization: Graphical Enumeration and Voting Methods , 1994, IEEE Trans. Syst. Man Cybern. Syst..

[31]  Lance R. Williams,et al.  Stochastic Completion Fields: A Neural Model of Illusory Contour Shape and Salience , 1997, Neural Computation.

[32]  Anil K. Jain,et al.  Image retrieval using color and shape , 1996, Pattern Recognit..

[33]  Simone Santini,et al.  Similarity Matching , 1995, ACCV.

[34]  Ming-Kuei Hu,et al.  Visual pattern recognition by moment invariants , 1962, IRE Trans. Inf. Theory.

[35]  R. J. Watt Issues in shape perception , 1993, Image Vis. Comput..

[36]  Thierry Pun,et al.  A Comparison of Human and Machine Assessments of Image Similarity for the Organization of Image Databases , 1997 .

[37]  Austin,et al.  An integrated framework for trademark image retrieval using gestalt features and CMM neural network , 1999 .

[38]  John P. Eakins,et al.  Evaluation of a Trademark Image Retrieval System , 1997, BCS-IRSG Annual Colloquium on IR Research.

[39]  A. Tversky Features of Similarity , 1977 .