CHILD:基于直方图的鲁棒高效图像局部描述符

Sai Hareesh Anamandra, V. Chandrasekaran
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引用次数: 2

摘要

设计鲁棒的图像局部描述符用于模式识别和分类一直是一个活跃的研究领域。为此,最近提出了一些基于韦伯定律的局部描述符。其中比较著名的有Weber局部描述子(WLD)、Weber局部二元模式(WLBP)和Gabor Weber局部描述子(GWLD)。实验表明,在嘈杂的环境下,它们无法对图案进行分类。我们的分析表明,为了鲁棒性和计算效率,需要重新设计WLD的组成部分:微分激励和方向。
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CHILD: A robust Computationally-Efficient Histogram-based Image Local Descriptor
Designing a robust image local descriptor for the purpose of pattern recognition and classification has been an active area of research. Towards this end, a number of local descriptors based on Weber's law have been proposed recently. Notable among them are Weber Local Descriptor (WLD), Weber Local Binary Pattern (WLBP) and Gabor Weber Local Descriptor (GWLD). Experiments reveal their inability to classify patterns under noisy environments. Our analysis indicates that the components of the WLD: differential excitation and orientation are to be redesigned for robustness and computational efficiency.
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