期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2015
卷号：3
期号：6
DOI：10.15680/ijircce.2015.0306023
出版社：S&S Publications
摘要：In this paper, we propose a simple, efficient, yet robust multiresolution approach to texture data rotationinvariant and noise tolerant. The proposed Resolution approach is very fast to build, solid while remaining robust toillumination variations, rotation changes, and noise. We develop a novel and simple strategy to compute a local binarydescriptor based on the conventional local binary pattern (LBP) approach, preserving the advantageous characteristicsof uniform LBP. Points are sampled in a circular neighbourhood, but keeping the number of bins in a single-scale LBPhistogram constant and small, such that arbitrarily large circular neighbour hoods can be sampled and efficientlyencoded over a number of scales. There is no requirement to learn a text on phrase book, as in methods based onclustering, and no tuning of parameters is required to deal with different data sets. Extensive investigational results onrepresentative texture databases show that the proposed text data not only demonstrates superior performance to anumber of recent state-of-the-art LBP variants under normal conditions, but also performs significantly andconsistently better in presence of noise due to its high distinctiveness and robustness. This noise robustnesscharacteristic of the proposed multi data is evaluated quantitatively with different artificially generated types and levelsof noise (including Gaussian, salt and pepper, and speckle noise) in natural texture images.
关键词：Local binary pattern; Gaussian filters; images; data set; robustness
