成对旋转不变的共生自适应完全局部三值模式Pairwise Rotation-Invariant Co-occurrence Adaptive Complete Local Ternary Pattern
陈晓文;刘光帅;刘望华;李旭瑞;
摘要(Abstract):
针对成对旋转不变的共生局部二值模式(PRICoLBP)旋转不变性较差及其相关改进算法EPRICoELBP对光照变化和噪声干扰较为敏感的问题,提出了一种增强成对旋转不变的共生自适应阈值完全局部三值模式。通过自适应阈值局部三值模式(ALTP)将图像分成Upper和Lower模式;分别在两种模式中找出像素点LBP特征极大、极小值对应的邻域起始编码点,利用中心像素点与其LBP特征极大、极小值对应的邻域起始编码点作为方向矢量,来确定中心像素点的上下文共生点对;利用自适应阈值完全局部三值模式(ACLTP)提取Upper和Lower模式中共生点对的局部纹理信息;联合上下文共生点对的特征直方图训练卡方核支持向量机,进行纹理图像识别检测。在应用广泛的Brodatz、Outex(TC10、TC12-h、TC12-t、TC14)、CUReT、KTH_TIPS、UIUC标准纹理库中,该算法相较于原始的PRICoLBP算法和其他算法在分类准确率上均有一定的提升,且在添加了高斯噪声和椒盐噪声的KTH_TIPS纹理库中,该算法依旧保持了较高的分类准确率。实验结果表明,该算法对旋转、光照变化和噪声干扰具有较强的鲁棒性。
关键词(KeyWords): 共生点对;局部三值模式;成对旋转不变;噪声鲁棒性;自适应阈值
基金项目(Foundation): 国家自然科学基金(51275431);; 四川省科技支撑计划项目(2015GZ0200)
作者(Author): 陈晓文;刘光帅;刘望华;李旭瑞;
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DOI:
参考文献(References):
- [1]刘丽,谢毓湘,魏迎梅,等.局部二进制模式方法综述[J].中国图象图形学报,2014,19(12):1696-1720.
- [2] VARGAS J F,FERRER M A,TRAVIESO C M,et al.Off-line signature verification based on grey level information using texture features[J].Pattern Recognition,2010,44(2):375-385.
- [3] HUANG A,ABUGHARBIEH R,TAM R.A novel rotationally invariant region-based hidden Markov model for efficient 3-D image segmentation[J].IEEE Transactions on Image Processing,2010,19(10):2737-2748.
- [4] CHOY S K,TONG C S.Statistical wavelet subband characterization based on generalized gamma density and its application in texture retrieval[J].IEEE Transactions on Image Processing,2010,19(2):281-289.
- [5] GALLOWAY M M.Texture analysis using gray level run lengths[J].Computer Graphics and Image Processing,1975,4(2):172-179.
- [6] OJALA T,PIETIKáNTEN M,HAWOOD D.A comparative study of texture measure with classification based on featured distributions[J].Pattern Recognition,1996,29(1):51-59.
- [7] LIU L,FIEGUTH P,GUO Y,et al.Local binary features for texture classification:Taxonomy and experimental study[J].Pattern Recognition,2017,62:135-160.
- [8] TAN X,TRIGGS B.Enhanced local texture feature sets for face recognition under difficult lighting conditions[J].IEEE Transactions on Image Processing,2010,19(6):1635-1650.
- [9] GUO Z,ZHANG L,ZHANG D.A completed modeling of local binary pattern operator for texture classification[J].IEEE Transactions on Image Processing,2010,19(6):1657-1663.
- [10] RASSEM T H,MOHAMMED M F,KHOO B E,et al.Performance evaluation of Completed Local Ternary Patterns(CLTP)for medical,scene and event image categorisation[C]//Proceedings of the 4th International Conference on Software Engineering and Computer Systems,2015:33-38.
- [11] RASSEM T H,MAKBOL N M,YEE S Y.Face recognition using Completed Local Ternary Pattern(CLTP)texture descriptor[J].International Journal of Electrical and Computer Engineering,2017,7(3):1594.
- [12] LIU L,ZHAO L,LONG Y,et al.Extended local binary patterns for texture classification[J].Image and Vision Computing,2012,30(2):86-99.
- [13] LIU L,LAO S,FIEGUTH P W,et al.Median robust extended local binary pattern for texture classification[J].IEEE Transactions on Image Processing,2016,25(3):1368-1381.
- [14] QI X,XIAO R,GUO J,et al.Pairwise rotation invariant co-occurrence local binary pattern[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2014,36(11):2199-2213.
- [15]高攀,刘光帅,马子恒,等.增强成对旋转不变的共生扩展局部二值模式[J].中国图象图形学报,2018,23(7):1024-1032.
- [16] OJALA T,PIETIKAINEN M,MAENPAA T.Multiresolution gray-scaleand rotation invariant texture classification with local binary patterns[J].IEEE Transactions on Pattern Analysis and MachineIntelligence,2002,24(7):971-987.
- [17] ITO S,KUBOTA S.Object classification using heterogeneous co-occurrence features[C]//Proceedings of European Conference on Computer Vision,2010:701-714.
- [18] YANG S,CHEN M,POMERLEAU D,et al.Food recognition using statistics of pairwise local features[C]//Proceedings of 2010 IEEE Computer Society Conference on Computer Vision and Pattern Recognition,2010:2249-2256.