Abstract
A study and results about pixelized images recognition in simulated prosthetic vision were presented. Twenty object and five scene images were chosen from the databases which were almost familiar by everyone. Two kinds of image processing methods (binarization directly and edge extraction from low resolution images), two common shapes of pixel (square and circular) and six pixels numbers(8×8, 16×16, 24×24, 32×32, 48×48 and 64×64) were used to form pixelized images and presented on head-mounted display (HMD) one by one. According to the trials, the mean recognition accuracy increased with the increase of pixel array number. The threshold of objects recognition was within the interval of 16×16 to 24×24. For simple scenes, it was between 32×32 and 48×48. The images with the threshold resolution, binarization method and circular pixel shape have shown the best results for recognition.
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© 2008 Springer-Verlag Berlin Heidelberg
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Zhao, Y., Tian, Y., Liu, H., Ren, Q., Chai, X. (2008). Pixelized Images Recognition in Simulated Prosthetic Vision. In: Peng, Y., Weng, X. (eds) 7th Asian-Pacific Conference on Medical and Biological Engineering. IFMBE Proceedings, vol 19. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-79039-6_123
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DOI: https://doi.org/10.1007/978-3-540-79039-6_123
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