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Voting-Based Matching for Near-Planar Objects with Drastic Illumination Variation

机译:具有剧烈照明变化的近平面物体基于投票的匹配

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Image registration is a challenging task when illumi-nation changes drastically. In this paper, we propose a novel algorithm, APCurve, to address this problem. APCurve matches all principle curves extracted from the sensed image and reference image based on voting matrix. All principal curves are extracted because they are robust against illumination change. Voting matrix is a simple method to match all principal curves. We test APCurve on a set of images taken under drastically changed illumination condition, and experimental results show it is effective and fast. An experimental comparison between APCurve and SURF[8] is presented, which shows APCurve outperforms SURF when the object is textureless. Finally, the successful application of APCurve in highlight removal task proves that our approach is useful in real practice.
机译:当照明急剧变化时,图像配准是一项具有挑战性的任务。在本文中,我们提出了一种新颖的算法APCurve来解决此问题。 APCurve基于投票矩阵匹配从感测图像和参考图像中提取的所有原理曲线。提取所有主要曲线是因为它们对光照变化具有鲁棒性。投票矩阵是一种匹配所有主要曲线的简单方法。我们在剧烈变化的照明条件下拍摄的一组图像上测试了APCurve,并且实验结果表明它是有效且快速的。进行了APCurve和SURF [8]的实验比较,表明当对象无纹理时,APCurve优于SURF。最后,APCurve在高光去除任务中的成功应用证明了我们的方法在实际操作中很有用。

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