NSCT子带纹理特征融合的中亚文种识别  

Script identification of central Asian based on fusion texture feature of NSCT sub-bands

作　　者：韩兴坤 阿力木江.艾沙[2] 努尔毕亚.亚地卡尔 朱亚俐[1] 库尔班.吾布力 HAN Xing-kun;Alimjan Aysa;Nurbiya Yadikar;ZHU Ya-li;Kurban Ubul(School of Information Science and Engineering,Xinjiang University,Urumqi 830046,China;Network and Information Center,Xinjiang University,Urumqi 830046,China)

机构地区：[1]新疆大学信息科学与工程学院,新疆乌鲁木齐830046 [2]新疆大学网络与信息中心,新疆乌鲁木齐830046

出　　处：《计算机工程与设计》2018年第9期2848-2855,共8页Computer Engineering and Design

基　　金：国家自然科学基金项目(61363064;61563052;61163028);新疆大学博士科研启动基金项目(BS150262)

摘　　要：由于中亚地区某些文种相似度较高,单一纹理特征不能充分描述它们的纹理特点。为此,提出基于NSCT子带纹理特征融合的文种识别方法,即先对预处理后的文档图像进行非下采样Contourlet变换。对变换产生的子带分别提取局部二值模式和灰度共生矩阵特征,生成高维融合特征向量,通过主成分分析法对其进行降维生成低维特征向量。通过对阿拉伯文、俄文、藏文、中文、维吾尔文、英文、蒙古文、吉尔吉斯斯坦文、哈萨克斯坦文、土耳其文进行实验,验证了该方法能更准确地提取文档图像多尺度、多方向的纹理特征,有效提高识别率。Due to the higher similarity of some scripts in Central Asia,a single texture feature can not adequately describe their texture feature.To solve this problem,a script-identification method based on fusion texture feature of nonsubsampled Contourlet transform sub-bands was proposed.The preprocessed document images were subjected to nonsubsampled Contourlet transform firstly.The local binary patterns and the gray level co-occurrence matrix features were extracted from the sub-bands gene rated by the transformation,and the high-dimensional fusion feature vector was generated.The principal component analysis was used to reduce dimension to generate low-dimensional feature vectors.Experiments on Arabic,Russian,Tibetan,Chinese,Uyghur,English,Mongolian,Kyrgyzstan,Kazakhstan,and Turkish verify that the proposed method can more accurately extract the multi-scale and multi-directional texture features of document images,and can improve the recognition rate effectively.

关 键 词：文种识别 融合纹理特征 非下采样CONTOURLET变换 局部二值模式 灰度共生矩阵 支持向量机 

分 类 号：TP391.4[自动化与计算机技术—计算机应用技术]