3D Object Recognition Using Kernel Construction of Phase Wrapped Images

摘要：

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.

关键词： Phase unwrapping 3D reconstruction image processing algorithm

作者: Hong Zhang Hongjun Su

作者单位: Department of Computer Science & Information Technology,Armstrong Atlantic State University, 11935 Abercorn Street, Savannah, GA 31419 USA

会议类型: 国际会议

会议名称: Third International Conference on Digital Image Processing(ICDIP 2011)(第三届数字图像处理国际会议)

会议地点: 成都

会议语种:英文

页码: 103-107

在线出版日期: 2011-04-15（万方平台首次上网日期，不代表论文的发表时间）