Statistical Analysis and Psychological Evaluation of Surfaces under Various Illuminations

Abstract:

Perceptions of image surface are very challenging work for computer vision. Human can amazingly expert at recognizing the reflective properties of surfaces of various materials which a robot can not do easily so far. Smoothly we can differentiate a shiny metallic sphere from the plastic sphere of similar dimensions and structure. In this paper, various image surfaces are analyzed according to various image statistics for robot vision systems. Identification of synonymous objects under various real-world illumination or other environments are very daunting task. However, this is very challenging and crucial for machine vision systems. Both statistical analyses and human evaluation by various subjects under rigorous illumination conditions, we find significant improvement in our analysis and emphasis the importance of statistical evaluation of surfaces for computer vision. Our findings clearly demonstrate that skewness has direct resemblance with the surface glossiness-level. Intensity histogram also shows crucial clue for surface analysis.

• Periodical: Applied Mechanics and Materials (Volume 36)
• Pages: 422-429
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.36.422
• Online since: October 2010
• Authors: Hossain Shahera, Seiichi Serikawa
• Keywords: Intensity Histogram, Michelson Contrast, Skewness, Surface Analysis

References

[1] G. J. Ward: Measuring and modeling anisotropic reflection, SIGGRAPH, Vol. 26 (2), (1992), pp.265-272.

[2] E. H. Adelson: Image Statistics and surface perception, Proc. of SPIE-IS&T Electronic Imaging, SPIE Vol. 6806 (2008), pp.1-9.

[3] M. S. Landy: A gloss on surface properties, Nature, Vol. 447 (2007), pp.158-159.

[4] R. O. Dror, A. S. Willisky and E. H. Edelson: Statistical characterization of real-world illumination, Journal of Vision, Vol. 4 (2004), pp.821-837.

[5] S. Nishida and M. Shinya: Use of image-based information in judgments of surface reflectance, Journal of the Optical Society of America, Vol. 15 (1998), pp.2951-2965.

DOI: 10.1364/josaa.15.002951

[6] R. W. Fleming, R. O. Dror and E. H. Adelson: Real-world illumination and the perception of surface reflectance properties. Journal of Vision, Vol. 3, No. 5 (2003), pp.347-368.

DOI: 10.1167/3.5.3

[7] I. Motoyoshi, S. Nishida and E. H. Adelson: Adaptation to skewed image statistics alters perception of glossiness and lightness, European Conference on Visual Perception, (2005) p.24. http: /www. perceptionweb. com/ecvp05/0168. html.

[8] I. Motoyoshi, S. Nishida and E. H. Adelson: Image statistics as a determinant of reflectance estimation, Vision Sciences Society Annual Meeting Abstracts, 2005. http: /journalofvision. org/5/8/569.

DOI: 10.1167/5.8.569

[9] L. Sharan, Y. Li, I. Motoyoshi, S. Nishida and E. H. Adelson: Image statistics for surface reflectance perception, Journal of Optical Society America, Vol. 25, No. 4 (2008).

DOI: 10.1364/josaa.25.000846

[10] I. Motoyoshi, S. Nishida, L. Sharan and E. H. Adelson: Image statistics and the perception of surface qualities, nature, Vo. 447 (2007), pp.206-209.

DOI: 10.1038/nature05724

[11] W. Burger & J. Burge: Principles of Digital Image Processing, Springer-Verlag London Limited (2009).

[12] S. R. Marschner, S. H. Westin, E. P. F. Lafortune, K. E. Torrance and D. P. Greenberg: Image-based BRDF measurement including human skin, In Proceedings of 10th Eurographics Workshop on Rendering, (1999), pp.139-52.

DOI: 10.1007/978-3-7091-6809-7_13

[13] E. H. Adelson: Lightness perception and lightness illusions, in M. Gazzaniga, Editor, The Cognitive Neurosciences, MIT Press, Cambridge, MA, (2000), pp.339-351.