標題: Perspective-transformation-invariant generalized Hough transform for perspective planar shape
作者: Lo, RC
Tsai, WH
資訊工程學系
Department of Computer Science
關鍵字: generalized Hough transform;perspective transformation invariant;perspective reference table;point spread function;Hough counting space;cell value incrementation;inverse generalized Hough transformation
公開日期: 1-Mar-1997
摘要: In the real world, most object shapes are perspectively transformed when imaged. How to recognize or locate such shapes in images is interesting and important. The conventional generalized Hough transform (GHT) is useful for detecting or locating translated two-dimensional (2D) planar shapes. However, it cannot be used for detecting perspectively transformed planar shapes. A new version of the GHT, called perspective-transformation-invariant generalized Hough transform (PTIGHT), is proposed to remove this weakness. The PTIGHT is based on the use of a new perspective reference table that is built up by applying both forward and inverse perspective transformations on a given template shape image from all viewing directions and positions. Due to the use of the point spread function to express the perspective reference table, the required dimensionality of the Hough counting space (HCS) for the PTIGHT is reduced to 2D. After performing the PTIGHT on an input image, the peaks in the HCS whose values are larger than a threshold is picked out as the candidate locations of the perspective shape to be detected in the input images. By performing an inverse PTIGHT on the candidates, one of the candidate locations whose corresponding shape marches best with the input shape is selected and the desired parameters of the perspective transformation can be obtained. Some experimental results are included to demonstrate the applicability of the proposed PTIGHT. (C) 1997 Pattern Recognition Society.
URI: http://dx.doi.org/10.1016/S0031-3203(96)00094-5
http://hdl.handle.net/11536/149502
ISSN: 0031-3203
DOI: 10.1016/S0031-3203(96)00094-5
期刊: PATTERN RECOGNITION
Volume: 30
起始頁: 383
結束頁: 396
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