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基于粗糙粒模型的图像纹理识别和检索

, PP. 225-229

Keywords: 粗糙粒,粒的边缘,分层熵,纹理识别

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Abstract:

传统的纹理识别方法大多是对图像频谱的研究,文中尝试以粒计算理论为基础,利用分层思想对图像的纹理特征进行识别。首先,通过引入粒的边缘和分层熵的概念,建立粗糙粒理论,构造粗糙粒度空间模型。然后,构建基于粒的边缘和分层熵的相似度计算方法,得出一种图像纹理识别方法。该方法不仅提高模型在图像纹理识别上的实用性,而且通过对识别和检索过程的同步进行简化纹理识别的计算过程。最后,仿真实验表明,该模型及所用到的相关方法是可行的,与其它方法相比,该方法识别和检索效果较好。

References

[1]  Miao Duoqian,Wang Guoyin,Liu Qing.Granular Computing: Past,Present and Prospects.Beijing,China: Science Press,2007(in Chinese)(苗夺谦,王国胤,刘 清.粒计算:过去、现在与展望.北京:科学出版社,2007)
[2]  Stepaniuk J,Skowron A.Ontological Framework for Approximation // Proc of the 10th International Conference on Rough Sets,Fuzzy Sets,Data Mining,and Granular Computing.Regina,Canada,2005: 718-727
[3]  Slowinski R,Vanderpooten D.A Generalized Definition of Rough Approximations Based on Similarity.IEEE Trans on Knowledge and Data Engineering,2000,12(2): 331-336
[4]  Doherty P,Grabowski M,Lukaszewicz W,et al.Towards a Framework for Approximate Ontologies.Fundamental Information,2003,57(2): 147-165
[5]  Antón-Rodríguez M,Díaz-Pernas F J,Díez-Higuera J F,et al.Recognition of Coloured and Textured Images through a Multi-Scale Neural Architecture with Orientational Filtering and Chromatic Diffusion.Neurocomputing,2009,72(16/17/18): 3713-3725
[6]  Ilea D E,Whelan P F.Image Segmentation Based on the Integration of Color-Texture Descriptors-A Review.Pattern Recognition,2011,44(10/11): 2479-2501
[7]  Zheng Zheng.Image Texture Recognition Based on Tolerance Granular Space.Journal of Chongqing University of Posts and Telecommunications: Natural Science Edition,2009,21(4): 484-489 (in Chinese)(郑 征.基于相容粒度空间模型的图像纹理识别.重庆邮电大学学报:自然科学版,2009,21(4): 484-489)
[8]  Wang Xiangyang,Chen Jingwei,Yu Yongjian.An Edge-Based Color Image Retrieval by Using Multiple Features.Pattern Recognition and Artificial Intelligence,2010,23(2): 216-221 (in Chinese)(王向阳,陈景伟,于永健.一种基于彩色边缘综合特征的图像检索算法.模式识别与人工智能,2010,23(2): 216-221)
[9]  Deselaers T,Keysers D,Ney H.Features for Image Retrieval: An Experimental Comparison.Information Retrieval,2008,11(2): 77-107
[10]  Chen Bo,Dai Qiuping.Image Segmentation Based on Geometric Active Contour Model.Pattern Recognition and Artificial Intelligence,2010,23(2): 186-190 (in Chinese)(陈 波,代秋平.基于几何活动轮廓模型的图像分割.模式识别与人工智能,2010,23(2): 186-190)
[11]  Kolaczyk E D,Ju J,Gopal S.Multiscale,Multigranular Statistical Image Segmentation.Journal of the American Statistical Association,2005,100(472): 1358-1369
[12]  Gandhi V,Kang J M,Shekhar S.Context Inclusive Function Evaluation: A Case Study with EM-Based Multi-Scale Multi-Granular Image Classification.Knowledge and Information Systems,2009,21(2): 231-247
[13]  Xu Jiucheng,Li Xiaoyan,Li Shuangqun,et al.Feature Images Retrieval Method of Tolerance Granular-Based Multi-Level Texture.Journal of Guangxi Normal University: Natural Science Edition,2011,29(1): 186-190 (in Chinese)(徐久成,李晓艳,李双群,等.基于相容粒的多层次纹理特征图像检索方法.广西师范大学学报:自然科学版,2011,29(1): 186-190)
[14]  Yao Xiaokun,Qiu Taorong,Bai Xiaoming.Granular Computing Method Based on Access to Approximate Ontology.Journal of Nanchang University: Natural Science,2009,33(6): 595-598 (in Chinese)(姚晓昆,邱桃荣,白小明.近似本体获取的粒计算方法.南昌大学学报: 理科版,2009,33(6): 595-598)
[15]  Lei Baoquan,Yang Lihua,Cheng Yongmei,et al.Natural Object Recognition Algorithm Based on SVM and Color/ Texture Combination Features.Computer Science,2009,36(10): 274-277 (in Chinese)(雷宝权,杨丽华,程咏梅,等.基于 SVM与颜色/纹理组合特征的景物识别算法.计算机科学,2009,36(10): 274-277)

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