计算机科学 ›› 2019, Vol. 46 ›› Issue (3): 125-130.doi: 10.11896/j.issn.1002-137X.2019.03.018
刘晓虹,朱玉全,刘哲,宋余庆,朱,彦,袁德琪
LIU Xiao-hong, ZHU Yu-quan, LIU Zhe, SONG Yu-qing, ZHU Yan, YUAN De-qi
摘要： 针对高阶方向导数局部二值模式(DLBP)算法会丢失部分高尺度邻域信息的缺陷,提出一种基于改进多尺度LBP算法(MSLBP)的肝脏CT图像特征提取方法。该方法首先对肝脏CT图像进行预处理,并提取正异常ROI区域,然后利用改进的多尺度LBP特征提取方法提取特征,将高阶尺度采样点信息融合其邻域相关点信息作为该采样点的最终信息参与运算,同时利用对角线区域求平均操作,突出了邻域像素点之间的关系特征,从更大范围描述肝脏图像的纹理信息,最后进行分类。实验结果表明:所提方法的准确率可达到90.1%,相比原始的LBP特征提取方法提高了8.7%,有一定的临床应用意义,可用于医生的辅助诊断。
中图分类号:
| [1]HAN J,MA K K.Rotation-invariant and scale-invariant gabor features for texture image retrieval.Image Vision Computing,2007,25(9):1474-1481. [2]MANJUNATH B S,MA W Y.Texture features for browsing and retrieval of image data.IEEE Transactions on Pattern Analysis and Machine Intelligence,1996,18(8):837-842. [3]VARMA M,ZISSERMAN A.A statistical approach to texture classification from single images.Kluwer Academic Publi-shers,2005,62(1-2):61-81. [4]VARMA M,ZISSERMAN A.A statistical approach to material classification using image patch exemplars.IEEE Transactions on Pattern Analysis and Machine Intelligence,2009,31(11):2032-2047. [5]SUGANYA R,RAJARAM S.Feature extraction and classification of ultrasound liver images using haralick texture-primitive features:Application of SVM classifier∥2013 International Conference on Recent Trends in Information Technology (ICRTIT).Chennai,2013:596-602. [6]ZHANG X,GAO X,LIU B J,et al.Effective staging of fibrosis by the selected texture features of liver:Which one is better,CT or MR imaging?.Computerized Medical Imaging & Grap-hics,2015,46:227-236. [7]KVOSTIKOV A V,KRYLOV A S,KAMALOY U R.Ultrasound image texture analysis for liver fibrosis stage diagnostics.Programming & Computer Software,2015,41(5):273-278. [8]VIJAYALAKSHMI B,BARATHI V S.Classification of CT Liver Images Using Local Binary Pattern with Legendre Moments.Current Science,2016,110(4):687-691. [9]OJALA T,PIETIKAINEN M,MAENPAA T.Multiresolution gray-scale and rotation invariant texture classification with local binary patterns.IEEE Transactions on Pattern Analysis and Machine Intelligence,2002,24(7):971-987. [10]LIU L,LONG Y,FIEGUTH P W,et al.BRINT:Binary rotation invariant and noise tolerant texture classification.IEEE Transactions on Image Processing,2014,23(7):3071-3084. [11]RAMAMOORTHY S,KIRUBAKARAN R,SUBRAMANIAN R S.Texture feature extraction using mgrlbp method for medical image classification∥Artificial Intelligence and Evolutionary Algorithms in Engineering Systems.India:Springer,2015:747-753. [12]YASAR H,CEYLAN M.A new method for extraction of ima- ge’s features:Complex discrete Ripplet-II transform∥2016 24th Signal Processing and Communication Application Con-ference.IEEE,2016:1673-1676. [13]LI X,PLATANIOTIS K N.Color texture representation using circular-processing based Hue-LBP for histo-pathology image analysis∥2016 IEEE International Conference on Image Processing (ICIP).Phoenix,AZ,2016:3573-3577. [14]JAISWAL A K,BANKA H.Local pattern transformation based feature extraction techniques for classification of epileptic EEG signals.Biomedical Signal Processing and Control,2017,34:81-92. [15]LIU L,FIEGUTH P,GUO Y,et al.Local binary features for texture classification:Taxonomy and experimental study.Pattern Recognition,2017,62:135-160. [16]TABATABAEI S M,CHALECHALE A.Using DLBP texture descriptors and SVM for Down syndrome recognition∥International Econference on Computer and Knowledge Enginee-ring.IEEE,2014:554-558. [17]LIU Z,ZHANG X L,SONG Y Q,et al.Liver segmentation with improved U-Net and Morphsnakes algorithm.Journal of Ima-ge and Graphics,2018,23(8):1254-1262. [18]FLETCHER R,FLECTHER S,FLECTHER G.Clinical epidemiology:the essentials(4th ed).Baltimore:Lippincott Williams & Wilkins,2012:45-83. [19]GUO Z,ZHANG L,ZHANG D.A completed modeling of local binary pattern operator for texture classification.IEEE Transactions on Image Processing,2010,19(6):1657-1663. [20]WOLF L,HASSNER T,TAIGMAN Y.Effective Unconst- rained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics.IEEE Transactions on Pattern Analysis & Machine Intelligence,2011,33(10):1978-1990. [21]MEHTA R,EGIAZARIAN K.Dominant Rotated Local Binary Patterns (DRLBP) for texture classification☆.Pattern Re-cognition Letters,2016,71(99):16-22. |
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