Please wait a minute...
浙江大学学报(工学版)
自动化技术、电信技术     
自适应书法字图像匹配和检索章
夏芬1, 张龙海2, 韩德志1, 毕坤1
1. 上海海事大学 信息工程学院,上海 201306;2.中海网络科技股份有限公司,上海 200135
Adaptive matching and retrieval for calligraphic character
ZHANG Xia fen1, ZHANG Long hai2, HAN De zhi1, BI Kun1
1. Information Engineering College, Shanghai Maritime University, Shanghai 201306, China;2. China Shipping Network Technology Limited Company, Shanghai 200135, China
 全文: PDF(2786 KB)   HTML
摘要:

为了解决基于形状匹配的书法字检索计算量大、耗时长、效率低的问题,提出根据样本字特征动态改变剪枝范围的自适应匹配法.离线统计分析数据库中书法字的各特征值分布范围;当用户提交查询样本字后,在线计算查询样本字中各个特征的显著因子,根据不同的显著性因子自适应获取可能相似的候选字集合;利用轮廓形状相似性算法在候选字中进行精确匹配,用匹配值排序检索结果.实验结果表明,与单纯的形状匹配法相比,该方法在提高查全率与查准率的同时,将平均检索时间缩短至5%左右;与层次式匹配法相比,该方法在运行时间上没有明显缩短,平均查全率和查准率提高10%左右.

Abstract:

An adaptive matching algorithm was proposed according to discrimination power of each visual feature in order to overcome the large computing and time consuming in shape based calligraphy character matching. Each feature value’s distribution range was analyzed statistically off line. When a query was submitted, its features were extracted and the corresponding significance factors were computed based on which self adaptive algorithm was employed to find a shortened list of possible similar candidates from the database. Then contour shape matching was run on the shortened list to rank and display the similar. The experimental results showed that the adaptive matching approach shortened the retrieval time to 5% of the original shape matching approach. The approach didn’t significantly speed up the retrieval, but raised the precision ratio about 10% on the condition of the same recall ratio compared with the hierarchical approach.

出版日期: 2016-04-01
:  TP 391  
基金资助:

国家自然科学基金资助项目(61303100);上海海事大学校基金资助项目(20130467).

作者简介: 章夏芬(1977—),女,讲师,从事图像处理、模式识别的研究. ORCID: 0000 0001 9287 8029. E-mail: xfzhang@shmtu.edu.cn
服务  
把本文推荐给朋友
加入引用管理器
E-mail Alert
RSS
作者相关文章  

引用本文:

夏芬, 张龙海, 韩德志, 毕坤. 自适应书法字图像匹配和检索章[J]. 浙江大学学报(工学版), 10.3785/j.issn.1008-973X.2016.04.023.

ZHANG Xia fen, ZHANG Long hai, HAN De zhi, BI Kun. Adaptive matching and retrieval for calligraphic character. JOURNAL OF ZHEJIANG UNIVERSITY (ENGINEERING SCIENCE), 10.3785/j.issn.1008-973X.2016.04.023.

链接本文:

http://www.zjujournals.com/eng/CN/10.3785/j.issn.1008-973X.2016.04.023        http://www.zjujournals.com/eng/CN/Y2016/V50/I4/766

[1] SETLUR V, STONE M C. A linguistic approach to categorical color assignment [J]. IEEE Transactions on Visualization and Computer Graphics, 2016, 22(1): 45-49.
[2] LIU L, FIEGUTH P W. Texture classification from random features [J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 2012, 34(3): 574-586.
[3] BERRETTI S, BIMBO A D, PALA P. Retrieval by shape similarity with perceptual distance and effective indexing [J]. IEEE Transaction on Multimedia, 2000,2(4): 225-239.
[4] 潘云鹤, 吴飞. 网上多媒体信息分析与检索[M]. 北京: 清华大学出版社, 2002: 28-37.
[5] PLAMONDON R, SRIHARI S N. Online and off line handwriting recognition: a comprehensive survey [J]. PatternAnalysis and Machine Intelligence, 2000, 22(1): 63-84.
[6] RATH T M, KANE S, LEHMAN A, et al. Indexing for a digital library of George Washington’s manuscripts: a study of word matching techniques [R]. Massachusetts: University of Massachusetts, 2004.
[7] ITAY Y, KLARA K, MALACHI B A, et al. Classification of Hebrew calligraphic handwriting styles: preliminary results [C]∥Proceedings of the 1st International Workshop on Document Image Analysis for Libraries. Palo Alto: [s. n.], 2006: 299-305.
[8] 冯兵,丁晓青.HMM方法识别脱机手写汉字[J].模式识别与人工智能,2002, 15(1): 84-88.
FENG Bing, DING Xiao qing. Off line handwriting Chinese character recognition [J]. Journals of Pattern Recognition and Artificial Intelligence, 2002, 15(1): 84-88.
[9] 马龙龙,刘成林.基于统计部首模型的联机手写汉字识别方法[J].智能系统学报, 2010, 5(5): 385-391.
MA Long long, LIU Cheng lin. On line handwritten Chinese character recognition using statistical radical models [J]. CAAI Transactions on Intelligent Systems, 2010, 5(5): 385-391.
[10] Chinese calligraphy character recognition of CADAL [EB/OL]. [2015 12 16]. http:∥www.cadal.zju.edu.cn/ Calligraphy.
[11] 章夏芬,庄越挺,鲁伟明,等.根据形状相似性的书法内容检索[J].计算机辅助设计与图形学学报, 2005,17 (11): 2565-2569.
ZHANG Xia fen, ZHUANG Yue ting, LU Wei ming, et al. Shape based calligraphy image retrieval [J]. Journal of Computer Aided Design and Computer Graphics, 2005, 17 (11): 2565-2569.
[12] ZHANG X F, ZHUANG Y T, WU J Q, et al. Hierarchical approximate matching for retrieval of Chinese historical calligraphy character [J]. Computer Science and Technology, 2007, 22 (4): 633-640.
[13] 俞凯,吴江琴,庄越挺.基于骨架相似性的书法字检索[J].计算机辅助设计与图形学学报,2009, 21(6): 746-751.
YU Kai, WU Jiang qin, ZHUANG Yue ting. Calligraphic characters retrieval based on skeleton similarity [J]. Journal of Computer Aided Design and Computer Graphics, 2009, 21(6): 746-751.
[14] 俞凯,吴江琴.书法字快速多层检索方法[J].计算机辅助设计与图形学学报,2011, 23(8): 1415-1419.
YU Kai, WU Jiang qin. Fast multi level retrieval for calligraphic characters [J]. Journal of Computer Aided Design and Computer Graphics, 2011, 23(8): 1415-1419.
[15] 陈颉,朱福喜.根据骨架结构相似性的书法内容分层检索[J].小型微型计算机系统,2010, 31(1): 138-142.
CHEN Jie, ZHU Fu xi. Hierarchical matching for Chinese calligraphic retrieval based on skeleton similarity [J]. Journal of Chinese Computer Systems, 2010,31(1): 138-142.
[16] 庄毅,庄越挺,吴飞.基于数据网格的书法字k近邻查询[J].软件学报, 2006, 17(11): 2289-2301.
ZHUANG Yi, ZHUANG Yue ting, WU Fei.Answering k NN query of Chinese calligraphic character based on data grid [J]. Journal of Software, 2006, 17(11): 22892301.
[17] ZHANG X F, ZHUANG Y T. Dynamic time warping for Chinese calligraphic character matching and recognition [J]. Pattern Recognition Letter, 2012, 33(16): 22622269.
[18] RUI Y, HUANG S. T, MEHROTRA S. Content based image retrieval with relevance feedback in MARS [C]∥ Proceedings of IEEE International Conference on Image Processing. Santa Barbara: IEEE, 1997: II815-818.
[19] NAGY G, ZHANG X F. CalliGUI: interactive labeling of calligraphic character images [C]∥Proceedings of 11th International Conference on Document Analysis and Recognition. Beijing [s. n.], 2011: 977-981.
[20] ZHANG X F, NAGY G. The CADAL calligraphicdatabase [C]∥ Proceedings of the 2011 Workshop on Historical Document Imaging and Processing. Beijing:[s. n.], 2011: 37-42.

[1] 何雪军, 王进, 陆国栋, 刘振宇, 陈立, 金晶. 基于三角网切片及碰撞检测的工业机器人三维头像雕刻[J]. 浙江大学学报(工学版), 2017, 51(6): 1104-1110.
[2] 王桦, 韩同阳, 周可. 公安情报中基于关键图谱的群体发现算法[J]. 浙江大学学报(工学版), 2017, 51(6): 1173-1180.
[3] 尤海辉, 马增益, 唐义军, 王月兰, 郑林, 俞钟, 吉澄军. 循环流化床入炉垃圾热值软测量[J]. 浙江大学学报(工学版), 2017, 51(6): 1163-1172.
[4] 毕晓君, 王佳荟. 基于混合学习策略的教与学优化算法[J]. 浙江大学学报(工学版), 2017, 51(5): 1024-1031.
[5] 穆晶晶, 赵昕玥, 何再兴, 张树有. 基于凹凸变换与圆周拟合的重叠气泡轮廓重构[J]. 浙江大学学报(工学版), 2017, 51(4): 714-721.
[6] 黄正宇, 蒋鑫龙, 刘军发, 陈益强, 谷洋. 基于融合特征的半监督流形约束定位方法[J]. 浙江大学学报(工学版), 2017, 51(4): 655-662.
[7] 蒋鑫龙, 陈益强, 刘军发, 忽丽莎, 沈建飞. 面向自闭症患者社交距离认知的可穿戴系统[J]. 浙江大学学报(工学版), 2017, 51(4): 637-647.
[8] 王亮, 於志文, 郭斌. 基于双层多粒度知识发现的移动轨迹预测模型[J]. 浙江大学学报(工学版), 2017, 51(4): 669-674.
[9] 廖苗, 赵于前, 曾业战, 黄忠朝, 张丙奎, 邹北骥. 基于支持向量机和椭圆拟合的细胞图像自动分割[J]. 浙江大学学报(工学版), 2017, 51(4): 722-728.
[10] 戴彩艳, 陈崚, 李斌, 陈伯伦. 复杂网络中的抽样链接预测[J]. 浙江大学学报(工学版), 2017, 51(3): 554-561.
[11] 刘磊, 杨鹏, 刘作军. 采用多核相关向量机的人体步态识别[J]. 浙江大学学报(工学版), 2017, 51(3): 562-571.
[12] 郭梦丽, 达飞鹏, 邓星, 盖绍彦. 基于关键点和局部特征的三维人脸识别[J]. 浙江大学学报(工学版), 2017, 51(3): 584-589.
[13] 王海军, 葛红娟, 张圣燕. 基于核协同表示的快速目标跟踪算法[J]. 浙江大学学报(工学版), 2017, 51(2): 399-407.
[14] 张亚楠, 陈德运, 王莹洁, 刘宇鹏. 基于增量图形模式匹配的动态冷启动推荐方法[J]. 浙江大学学报(工学版), 2017, 51(2): 408-415.
[15] 刘宇鹏, 乔秀明, 赵石磊, 马春光. 统计机器翻译中大规模特征的深度融合[J]. 浙江大学学报(工学版), 2017, 51(1): 46-56.