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This article is part of the series Image and Video Processing for Disability.

Open Access Open Badges Research Article

Transforming 3D Coloured Pixels into Musical Instrument Notes for Vision Substitution Applications

Guido Bologna1*, Benoît Deville2, Thierry Pun2 and Michel Vinckenbosch1

Author Affiliations

1 University of Applied Science, Rue de la prairie 4, Geneva 1202, Switzerland

2 Computer Science Center, University of Geneva, Rue Général Dufour 24, Geneva 1211, Switzerland

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EURASIP Journal on Image and Video Processing 2007, 2007:076204  doi:10.1155/2007/76204

The electronic version of this article is the complete one and can be found online at: http://jivp.eurasipjournals.com/content/2007/1/076204

Received:15 January 2007
Accepted:23 May 2007
Published:22 August 2007

© 2007 Bologna et al.

This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

The goal of the See ColOr project is to achieve a noninvasive mobility aid for blind users that will use the auditory pathway to represent in real-time frontal image scenes. We present and discuss here two image processing methods that were experimented in this work: image simplification by means of segmentation, and guiding the focus of attention through the computation of visual saliency. A mean shift segmentation technique gave the best results, but for real-time constraints we simply implemented an image quantification method based on the HSL colour system. More particularly, we have developed two prototypes which transform HSL coloured pixels into spatialised classical instrument sounds lasting for 300 ms. Hue is sonified by the timbre of a musical instrument, saturation is one of four possible notes, and luminosity is represented by bass when luminosity is rather dark and singing voice when it is relatively bright. The first prototype is devoted to static images on the computer screen, while the second has been built up on a stereoscopic camera which estimates depth by triangulation. In the audio encoding, distance to objects was quantified into four duration levels. Six participants with their eyes covered by a dark tissue were trained to associate colours with musical instruments and then asked to determine on several pictures, objects with specific shapes and colours. In order to simplify the protocol of experiments, we used a tactile tablet, which took the place of the camera. Overall, colour was helpful for the interpretation of image scenes. Moreover, preliminary results with the second prototype consisting in the recognition of coloured balloons were very encouraging. Image processing techniques such as saliency could accelerate in the future the interpretation of sonified image scenes.


  1. RM Ruff, E Perret, Auditory spatial pattern perception aided by visual choices. Psychological Research 38(4), 369–377 (1976). PubMed Abstract | Publisher Full Text OpenURL

  2. S Lakatos, Recognition of complex auditory-spatial patterns. Perception 22(3), 363–374 (1993). PubMed Abstract | Publisher Full Text OpenURL

  3. A Hollander, in An exploration of virtual auditory shape perception, M, ed. by . S. thesis (University of Washington, Seattle, Wash, USA, 1994)

  4. L Kay, A sonar aid to enhance spatial perception of the blind: engineering design and evaluation. The Radio and Electronic Engineer 44(11), 605–627 (1974). Publisher Full Text OpenURL

  5. PBL Meijer, An experimental system for auditory image representations. IEEE Transactions on Biomedical Engineering 39(2), 112–121 (1992). PubMed Abstract | Publisher Full Text OpenURL

  6. C Capelle, C Trullemans, P Arno, C Veraart, A real-time experimental prototype for enhancement of vision rehabilitation using auditory substitution. IEEE Transactions on Biomedical Engineering 45(10), 1279–1293 (1998). PubMed Abstract | Publisher Full Text OpenURL

  7. J Cronly-Dillon, K Persaud, RPF Gregory, The perception of visual images encoded in musical form: a study in cross-modality information transfer. Proceedings of the Royal Society B 266(1436), 2427–2433 (1999). PubMed Abstract | Publisher Full Text | PubMed Central Full Text OpenURL

  8. JL Gonzalez-Mora, A Rodriguez-Hernandez, LF Rodriguez-Ramos, L Dfaz-Saco, N Sosa, Development of a new space perception system for blind people, based on the creation of a virtual acoustic space. Proceedings of International Work-Conference on Artificial and Natural Neural Networks (IWANN '99), June 1999, Alicante, Spain 2, 321–330

  9. P Roth, in Représentation multimodale d'images digitales dans des systèmes informatiques multimédias pour utilisateurs non-voyants, Ph, ed. by . D. thesis (Computer Vision and Multimedia Laboratory, University of Geneva, Geneva, Switzerland, 2002) PubMed Abstract | Publisher Full Text OpenURL

  10. SL Horowitz, T Pavlidis, Picture segmentation by a directed split and merge procedure. Computer Methods in Image Analysis (IEEE Press, New York, NY, USA, 1977), pp. 101–111

  11. E Forgy, Cluster analysis of multivariate data: efficiency versus interpretability of classifications. Biometrics 21(3), 768–769 (1965)

  12. J McQueen, Some methods for classification and analysis of multivariate observations. Proceedings of the 5th Berkeley Symposium on Mathematical Statistics and Probability, 1967, Berkeley, Calif, USA 1, 281–297

  13. K Fukunaga, Introduction to Statistical Pattern Recognition, 2nd edn. (Academic Press Professional, San Diego, Calif, USA, 1990)

  14. Y Cheng, Mean shift, mode seeking, and clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence 17(8), 790–799 (1995). Publisher Full Text OpenURL

  15. D DeCarlo, A Santella, Stylization and abstraction of photographs. Proceedings of the 29th Annual Conference on Computer Graphics and Interactive Techniques (SIGGRAPH '02), July 2002, San Antonio, Tex, USA, 769–776

  16. F Landragin, Saillance physique et saillance cognitive. Corela 2(2) (2004)

  17. DD Hoffman, M Singh, Salience of visual parts. Cognition 63(1), 29–78 (1997). PubMed Abstract | Publisher Full Text OpenURL

  18. R Milanese, in Detecting salient regions in an image: from biological evidence to computer implementations, Ph, ed. by . D. thesis (University of Geneva, Geneva, Switzerland, 1993)

  19. L Itti, C Koch, E Niebur, A model of saliency-based visual attention for rapid scene analysis. IEEE Transactions on Pattern Analysis and Machine Intelligence 20(11), 1254–1259 (1998). Publisher Full Text OpenURL

  20. T Kadir, M Brady, Scale, saliency and image description. International Journal of Computer Vision 45(2), 83–105 (2001). Publisher Full Text OpenURL

  21. DG Lowe, Object recognition from local scale-invariant features. Proceedings of the 7th IEEE International Conference on Computer Vision (ICCV '99), September 1999, Kerkyra, Greece 2, 1150–1157

  22. H Bay, T Tuytelaars, L van Gool, SURF: speeded up robust features. Proceedings of the 9th European Conference on Computer Vision (ECCV '06), May 2006, Graz, Austria, 404–417

  23. MA Gerzon, Design of ambisonic decoders for multispeaker surround sound. Journal of the Audio Engineering Society 25, 1064 (1977)

  24. JS Bamford, in An analysis of ambisonic sound systems of first and second order, M, ed. by . S. thesis (University of Waterloo, Waterloo, Ontario, Canada, 1995)

  25. DG Malham, A Myatt, 3-D sound spatialization using ambisonic techniques. Computer Music Journal 19(4), 58–70 (1995). Publisher Full Text OpenURL

  26. J Daniel, in Acoustic field representation, application to the transmission and the reproduction of complex sound environments in a multimedia context, Ph, ed. by . D. thesis (University of Paris 6, Paris, France, 2000)

  27. G Bologna, M Vinckenbosch, Eye tracking in coloured image scenes represented by ambisonic fields of musical instrument sounds. Proceedings of the 1st International Work-Conference on the Interplay Between Natural and Artificial Computation (IWINAC '05), June 2005, Las Palmas, Spain, 327–337

  28. VR Algazi, RO Duda, DP Thompson, C Avendano, The CIPIC HRTF database. Proceedings of IEEE Workshop on the Applications of Signal Processing to Audio and Acoustics (WASPAA '01), October 2001, New Platz, NY, USA, 99–102