3D object recognition using kernel construction of phase wrapped images

Hong Zhang; Hongjun Su

doi:10.1117/12.896220

8 July 2011 3D object recognition using kernel construction of phase wrapped images

Hong Zhang, Hongjun Su

Proceedings Volume 8009, Third International Conference on Digital Image Processing (ICDIP 2011); 80090K (2011) https://doi.org/10.1117/12.896220
Event: 3rd International Conference on Digital Image Processing, 2011, Chengdu, China

Abstract

Kernel methods are effective machine learning techniques for many image based pattern recognition problems. Incorporating 3D information is useful in such applications. The optical profilometries and interforometric techniques provide 3D information in an implicit form. Typically phase unwrapping process, which is often hindered by the presence of noises, spots of low intensity modulation, and instability of the solutions, is applied to retrieve the proper depth information. In certain applications such as pattern recognition problems, the goal is to classify the 3D objects in the image, rather than to simply display or reconstruct them. In this paper we present a technique for constructing kernels on the measured data directly without explicit phase unwrapping. Such a kernel will naturally incorporate the 3D depth information and can be used to improve the systems involving 3D object analysis and classification.

Citation Download Citation

Hong Zhang and Hongjun Su "3D object recognition using kernel construction of phase wrapped images", Proc. SPIE 8009, Third International Conference on Digital Image Processing (ICDIP 2011), 80090K (8 July 2011); https://doi.org/10.1117/12.896220

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