局部方向模式(LDP)——一种用于目标识别的鲁棒图像描述符

T. Jabid, M. H. Kabir, O. Chae
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引用次数: 114

摘要

本文提出了一种新的局部特征描述符——局部定向模式(LDP),用于描述局部图像特征。通过计算每个像素位置上所有八个方向的边缘响应值并从相对强度大小生成代码来获得LDP特征。每个码位序列通过考虑局部邻域来确定,从而成为鲁棒噪声情况。介绍了一种旋转不变的LDP编码,该编码利用了最突出边缘响应的方向。最后,通过累积整个输入图像(或图像区域)上LDP特征的出现次数,形成图像描述符来描述图像(或图像区域)。在Brodatz纹理数据库上的实验结果表明,LDP显著优于其他常用的密集描述符(例如,Gabor-wavelet和LBP)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Local Directional Pattern (LDP) – A Robust Image Descriptor for Object Recognition
This paper presents a novel local feature descriptor, theLocal Directional Pattern (LDP), for describing localimage feature. A LDP feature is obtained by computing theedge response values in all eight directions at each pixelposition and generating a code from the relative strengthmagnitude. Each bit of code sequence is determined byconsidering a local neighborhood hence becomes robust innoisy situation. A rotation invariant LDP code is alsointroduced which uses the direction of the most prominentedge response. Finally an image descriptor is formed todescribe the image (or image region) by accumulating theoccurrence of LDP feature over the whole input image (orimage region). Experimental results on the Brodatz texturedatabase show that LDP impressively outperforms theother commonly used dense descriptors (e.g.,Gabor-wavelet and LBP).
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