计算机科学 ›› 2018, Vol. 45 ›› Issue (12): 206-209.doi: 10.11896/j.issn.1002-137X.2018.12.034
黄庆宇, 章登义
HUANG Qing-yu, ZHANG Deng-yi
摘要: 采用非量化的局部特征设计出一个稳健的纹理描述符,以便增强旋转和尺度变化时纹理分类的鲁棒性。首先,引入了局部特征的旋转对称性的概念,提出了一种新颖的局部特征来描述纹理的旋转不变特性。为了处理剧烈的旋转、尺度等变化,利用费舍尔向量编码方法对纹理特征量进行多尺度分析,在不增加局部特征维度的同时又能结合尺度信息,由此产生的局部特征对旋转、灰度变化都有较强的鲁棒性。实验结果表明,所提方法的评估结果在许多数据集上都远远超过了现有最优算法,大大提高了纹理分类的精度。
中图分类号:
[1]HARALICK R,SHANMUGAM K,DINSTEIN I.TexturalFeatures for Image Classification.IEEE Transactions on Systems Man & Cybernetics,1973,SMC3(6):610-621. [2]CROSS G,JAIN A.Markov random field texture models.IEEE Transactions on Pattern Analysis and Machine Intelligence,1983,5(1):25-39. [3]VARMA M,ZISSERMAN A.A Statistical Approach to Texture Classification from Single Images.International Journal of Computer Vision,2005,62(1/2):61-81. [4]CROSIER M,GRIFFIN L.Using Basic Image Features for Texture Classification.International Journal of Computer Vision,2010,88(3):447-460. [5]WU J,REHG J.Centrist:A Visual Descriptor for Scene Categorization.IEEE Transactions on Pattern Analysis and Machine Intelligence,2011,33(8):1489-1501. [6]OJALA T,PIETIKÄINEN M,MÄENPÄÄ 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. [7]SUN J D,MA Y Y.Research Summary of Texture Features .Computer System Applications,2010,19(6):245-250.(in Chinese) 孙君顶,马媛媛.纹理特征研究综述.计算机系统应用,2010,19(6):245-250. [8]LIU L,KUANG G Y.A Summary of Image Texture Feature Extraction Methods .Chinese Journal of Image and Gra-phics.2009,14(4):622-635.(in Chinese) 刘丽,匡纲要.图像纹理特征提取方法综述.中国图象图形学报,2009,14(4):622-635. [9]WU X S,SUN J D.Image Retrieval Based on Local Edge Two Value Model .Journal of Optoelectronics,Laser,2013,24(1):184-189.(in Chinese) 毋小省,孙君顶.基于局部边缘二值模式的图像检索.光电子·激光,2013,24(1):184-189. [10]WU X S,SUN J D.Image Retrieval Based on Improved Directional Texture Spectrum .Journal of Optoelectronics·Laser,2012,23(4):812-818.(in Chinese) 毋小省,孙君顶.基于改进方向纹理谱特征的图像检索.光电子·激光,2012,23(4):812-818. [11]TANG Y Y,MA H,XI D,et al.Modified Fractal Signature (MFS):A New Approach to Document Analysis for Automatic Knowledge Acquisition.IEEE Transactions on Knowledge &Data Engineering,1997,9(5):747-762. [12]WU X S.Improved Rotation Invariant Region Texture Descriptors.Journal of Optoelectronics·Laser,2011,22(5):783-787.(in Chinese) 毋小省.改进的旋转不变区域纹理谱描述符.光电子.激光,2011,22(5):783-787. [13]MEHTA R,EGIAZARIAN K.Texture Classification UsingDense Micro-block Difference (DMD)[C]∥Proceedings of AsianConference on Computer Vision.Springer,2014:643-658. [14]JIANG S,TANG G A,LIU K.The Method of Calculating Texture Regularity Using Cumulative Distance Matching Function .Journal of Computer Aided Design and Computer Graphics,2015,27(10):1874-1880.(in Chinese) 蒋圣,汤国安,刘凯.利用累加距离匹配函数的纹理规则度计算方法.计算机辅助设计与图形学学报,2015,27(10):1874-1880. [15]CALONDER M,LEPETIT V,STRECHA C,et al.Brief:Binary Robust Independent Elementary Features∥Proceedings of European Conference on Computer Vision.Springer Berlin Heidelberg,2010:778-792. [16]RUBLEE E,RABAUD V,KONOLIGE K,et al.ORB:An Efficient Alternative to Sift or Surf∥Proceedings of IEEE International Conference on Computer Vision.IEEE Press,2011,2564-2571. [17]WEYL H.Symmetry.Princeton,NJ,USA:Princeton Uni-versity Press,1952. [18]PERRONNIN F,SÁNCHEZ J,MENSINK T.Improving theFisher Kernel for Large-scale Image Classification∥Proceedings of European Conference on Computer Vision.2010:143-156. [19]CIMPOI M,MAJI S,KOKKINOS I,et al.Describing Textures in the Wild∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.IEEE Press,2014:3606-3613. [20]VARMA M,ZISSERMAN A.A Statistical Approach to Mate-rial Classification Using Image Patch Exemplars.IEEE Tran-sactions on Pattern Analysis and Machine Intelligence,2009,31(11):2032-2047. [21]QUAN Y,XU Y,SUN Y,et al.Lacunarity Analysis on Image Patterns for Texture Classification∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.IEEE Press,2014:160-167. [22]RYU J,HONG S,YANG H.Sorted Consecutive Local Binary Pattern for Texture Classification.IEEE Transactions on Image Processing,2015,24(7):2254-2265. [23]VARMA M,GARG R.Locally Invariant Fractal Features forStatistical Texture Classification∥Proceedings of IEEE International Conference on Computer Vision.IEEE Press,2007:1-8. [24]XU Y,YANG X,LING H,et al.A New Texture DescriptorUsing Multifractal Analysis in Multi-orientation Wavelet pyramid ∥Proceedings of IEEE Conference on Computer Vision and Pattern Recognition.IEEE Press,2010:161-168. [25]URBACH E R,ROERDINK J B,WILKINSON M H.ConnectedShape-size Pattern Spectra for Rotation and scale-invariant Classification of Gray-scale Images.IEEE Transactions on Pattern Analysis and Machine Intelligence,2007,29(2):272-285. [26]UL HUSSAIN S,TRIGGS B.Visual Recognition Using Local Quantized Patterns ∥Proceedings of European Conference on Computer Vision.Springer Berlin Heidelberg,2012:716-729. [27]CHEN J,SHAN S,HE C,et al.WLD:A Robust Local Image Descriptor.IEEE Transactions on Pattern Analysis and Machine Intelligence,2010,32(9):1705-1720. [28]SHARMA G,UL HUSSAIN S,JURIE F.Local Higher-order Statistics (LHS) for Texture Categorization and Facial Analysis ∥Proceedings of European Conference on Computer Vision.Springer Berlin Heidelberg,2012:1-12. |
[1] | 李宗民, 张玉鹏, 刘玉杰, 李华. 基于可变形图卷积的点云表征学习 Deformable Graph Convolutional Networks Based Point Cloud Representation Learning 计算机科学, 2022, 49(8): 273-278. https://doi.org/10.11896/jsjkx.210900023 |
[2] | 赵敏, 刘惊雷. 基于高斯场和自适应图正则的半监督聚类 Semi-supervised Clustering Based on Gaussian Fields and Adaptive Graph Regularization 计算机科学, 2021, 48(7): 137-144. https://doi.org/10.11896/jsjkx.200800190 |
[3] | 唐一星, 刘学亮, 胡社教. 多方向分区网络结构的行人再识别 Multi-orientation Partitioned Network for Person Re-identification 计算机科学, 2021, 48(10): 204-211. https://doi.org/10.11896/jsjkx.210300128 |
[4] | 朱威, 绳荣金, 汤如, 何德峰. 基于动态图卷积和空间金字塔池化的点云深度学习网络 Point Cloud Deep Learning Network Based on Dynamic Graph Convolution and Spatial Pyramid Pooling 计算机科学, 2020, 47(7): 192-198. https://doi.org/10.11896/jsjkx.190700180 |
[5] | 喻露, 胡剑锋, 姚磊岳. 全局块与局部块协作的相关滤波目标跟踪算法 Correlation Filter Object Tracking Algorithm Based on Global and Local Block Cooperation 计算机科学, 2020, 47(6): 157-163. https://doi.org/10.11896/jsjkx.190500078 |
[6] | 贺超雷,毕秀丽,肖斌. 一种基于Zernike矩的局部特征检测方法 Zernike Moment Based Approach for Local Feature Detection 计算机科学, 2020, 47(2): 135-142. https://doi.org/10.11896/jsjkx.181202403 |
[7] | 王岩, 罗倩, 邓辉. 基于变分贝叶斯的轴承故障诊断方法 Bearing Fault Diagnosis Method Based on Variational Bayes 计算机科学, 2019, 46(11): 323-327. https://doi.org/10.11896/jsjkx.180901719 |
[8] | 王亮,田萱. 单幅散焦图像的局部特征模糊分割算法 Local Feature Fuzzy Segmentation Algorithm for Single Defocused Image 计算机科学, 2018, 45(2): 318-321. https://doi.org/10.11896/j.issn.1002-137X.2018.02.055 |
[9] | 黄翀,郑河荣,潘翔. 局部特征自适应的DM二维码结构提取方法 Adaptive Module Localization Method of Local Feature for Data Matrix Code 计算机科学, 2014, 41(Z11): 95-99. |
[10] | 鲍程辉,朱康,贺新光. 基于非下采样Contourlet系数局部特征的遥感图像融合方法 Remote Sensing Image Fusion Method Based on Local Feature of Nonsubsampled Contourlet Coefficients 计算机科学, 2014, 41(3): 310-313. |
[11] | 梁晔,于剑,刘宏哲. 基于BoF模型的图像表示方法研究 Study of BoF Model Based Image Representation 计算机科学, 2014, 41(2): 36-44. |
[12] | 罗楠,孙权森,陈强,纪则轩,夏德深. 结合SURF特征点与DAISY描述符的图像匹配算法 Image Matching Algorithm Combining SURF Feature Point and DAISY Descriptor 计算机科学, 2014, 41(11): 286-290. https://doi.org/10.11896/j.issn.1002-137X.2014.11.056 |
[13] | 杨族桥,陈跃鹏,张青. 综合视觉注意模型的显著性局部特征提取算法研究 Salient Local Feature Extraction Algorithm Based on Integrated Visual Attention Model 计算机科学, 2013, 40(8): 289-292. |
[14] | 朱康,贺新光. 基于形态学和Contourlet系数区域特征的遥感图像融合方法 Remote Sensing Images Fusion Method Based on Morphology and Regional Feature of Contourlet Coefficients 计算机科学, 2013, 40(4): 301-305. |
[15] | 赵海英,徐光美,彭 宏. 纹理粗糙度度量算法的性能比较 Performance Evaluation for the Algorithms to Measure Texture Coarseness 计算机科学, 2011, 38(6): 288-292. |
|