Research Article Open Access

Quaternion Photometric Stereo for Rotation Invariant Surface Texture Classification

Balakrishnan Sathyabama1, Srinivan Raju1 and Abhaikumar Varadhan1
  • 1 Department of Electronics and Communication Engineering, Thiagarajar College of Engineering, Madurai, Tamil Nadu, India


Problem statement: The escalating growth of computer vision applications has increased the need for faster and more accurate image analysis algorithms. One application of image analysis that has been studied for a long time is texture analysis. The majority of existing texture analysis methods makes the explicit or implicit assumption that texture images are acquired from the same viewpoint. This study presents a rotationally invariant descriptor for textures with different orientations based on the Quaternion Representation. Approach: A novel Quaternion Photometric Stereo (QPS) was proposed for Rotation invariant classification of 3D surface textures. QPS was constructed by placing each pixel of three images of same texture with different orientation into the three imaginary parts of the quaternion, leaving the real part zero. The Peak Distribution Norm Vector (PDNV) was extracted from the radial plot of the Quaternion Fourier spectrum as rotation invariant texture signature used for texture classification. Results: The quaternion representation of stereo images was to be effective in the context of Rotation Invariant Texture classification. Conclusion: The proposed Quaternion approach gives a successful classification rate with computational advantages than the previously developed Monochrome and Color Photometric Stereo Methods.

American Journal of Applied Sciences
Volume 8 No. 10, 2011, 992-996


Submitted On: 20 November 2010 Published On: 20 August 2011

How to Cite: Sathyabama, B., Raju, S. & Varadhan, A. (2011). Quaternion Photometric Stereo for Rotation Invariant Surface Texture Classification. American Journal of Applied Sciences, 8(10), 992-996.

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  • Quaternion Fourier spectrum
  • radial plot
  • Peak Distribution Norm Vector (PDNV)
  • monochrome and color photometric stereo
  • Quaternion Photometric Stereo (QPS)