Adaptive Hough transform for the detection of natural shapes under weak affine transformations

被引:31
作者
Ecabert, O
Thiran, JP
机构
[1] Philips Res, D-52066 Aachen, Germany
[2] Tech Univ Darmstadt, D-64283 Darmstadt, Germany
[3] Swiss Fed Inst Technol, Signal Proc Inst, CH-1015 Lausanne, Switzerland
关键词
adaptive generalized Hough transform; affine transformation; object detection; local shape variability;
D O I
10.1016/j.patrec.2004.05.009
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper introduces a two-steps adaptive generalized Hough transform (GHT) for the detection of non-analytic objects undergoing weak affine transformations in images. The first step of our algorithm coarsely locates the region of interest with a GHT for similitudes. The returned detection is then used by an adaptive GHT for affine transformations. The adaptive strategy makes the computation more amenable and ensures high accuracy, while keeping the size of the accumulator array small. To account for the deformable nature of natural objects, local shape variability is incorporated into the algorithm in both the detection and reconstruction steps. Finally, experiments are performed on real medical data showing that both accuracy and reasonable computation times can be reached. (C) 2004 Elsevier B.V. All rights reserved.
引用
收藏
页码:1411 / 1419
页数:9
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