Advanced Search
Volume 41 Issue 10
Oct.  2015
Turn off MathJax
Article Contents
Journal of Beijing University of Aeronautics and Astronautics  > 2015  >  41(10): 1935-1942.
DENG Wei, WU Lingda, ZHANG Yougen, et al. Online sketch recognition for mixed point and irregular military symbols[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(10): 1935-1942. doi: 10.13700/j.bh.1001-5965.2014.0826(in Chinese)
Citation: DENG Wei, WU Lingda, ZHANG Yougen, et al. Online sketch recognition for mixed point and irregular military symbols[J]. Journal of Beijing University of Aeronautics and Astronautics, 2015, 41(10): 1935-1942. doi: 10.13700/j.bh.1001-5965.2014.0826(in Chinese)
shu

Online sketch recognition for mixed point and irregular military symbols

doi: 10.13700/j.bh.1001-5965.2014.0826
  • 1.

    Science and Technology on Complex Electronic System Simulation Laboratory, Academy of Equipment, Beijing 101416, China

  • 2. Department of Information Systems, Academy of National Defense Information, Wuhan 430010, China

  • 3. Institute of Information Technology of Guilin, Guilin 541004, China

  • Received Date: 30 Dec 2014
  • Rev Recd Date: 10 Apr 2015
  • Publish Date: 20 Oct 2015
    Abstract
  • Most of current research on online sketched military symbols recognition concerns only one type of symbols, point symbols or irregular symbols, using different methods to recognize separately. But in practical applications the two types of symbols are mixed. It becomes a major issue to find a way to recognize a type-unknown military symbol. A minimum spanning tree (MST) covering model-based mixed recognition method was proposed. In the training phase, two MST-based covering models were built for point and irregular symbols respectively. And then a two-class support vector machine (SVM) classifier was trained. In the recognition phase, the coarse type identification was accomplished by using the geometrical and structural information firstly. Then the confidence estimations were calculated and integrated to identify the type of the unknown symbol. Different types of symbols were classified by two existing modules. The algorithm was tested on 113 classes of point symbols and 36 classes of irregular symbols. The accuracy rate of symbol type identification was 94.7%, and the final recognition rate was 91.6% in real time.

     

    • FullText(HTML)
  • loading
    • References(21)
  • [1]
    Sun Z B,Wang C H,Zhang L Q,et al.Query-adaptive shape topic mining for hand-drawn sketch recognition[C]∥Proceedings of 20th ACM International Conference on Multimedia.New York:ACM,2012:519-528.
    [2]
    巩应奎,范玉青,吴志方.笔式草图的增量识别[J].北京航空航天大学学报,2006,32(5):621-624.Gong Y K,Fan Y Q,Wu Z F.Incremental recognition method for pen-based sketch[J].Journal of Beijing University of Aeronautics and Astronautics,2006,32(5):621-624(in Chinese).
    [3]
    陈鸿,汤晓安,杨耀明,等.基于位移映射的非规则军队标号绘制算法[J].计算机辅助设计与图形学学报,2011,23(5):797-804.Chen H,Tang X A,Yang Y M,et al.Using displacement mapping for irregular military symbols rendering[J].Journal of Computer-Aided Design & Computer Graphics,2011,23(5):797-804(in Chinese).
    [4]
    邓维,吴玲达,张友根,等.采用快速图元匹配的手绘非规则军标识别[J].计算机辅助设计与图形学学报,2014,26(10):1835-1843.Deng W,Wu L D,Zhang Y G,et al.Using fast primitive matching to recognize sketched irregular military marking symbols[J].Journal of Computer-Aided Design & Computer Graphics,2014,26(10):1835-1843(in Chinese).
    [5]
    吴玲达,张友根,邓维,等.面向手绘军标图形的旋转自由识别方法[J].中国图象图形学报,2014,19(3):456-462.Wu L D,Zhang Y G,Deng W,et al.Rotation free recognition of hand-drawn military marking symbols[J].Journal of Image and Graphics,2014,19(3):456-462(in Chinese).
    [6]
    Hammond T,Logsdon D,Peschel J,et al.A sketch recognition interface that recognizes hundreds of shapes in course-of-action diagrams[C]∥Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (CHI).New York:ACM,2010:4213-4218.
    [7]
    Cummings D,Fymat S,Hammond T.Sketch-based interface for interaction with unmanned air vehicles[C]∥Proceedings of the ACM SIGCHI Conference on Human Factors in Computing Systems,2012.
    [8]
    Deng W,Wu L D,Yu R H,et al.On-line sketch recognition using direction feature[C]∥Proceedings of Human-Computer Interaction (INTERACT 2013).Heidelberg:Springer Verlag,2013:259-266.
    [9]
    Delaye A,Liu C L.Contextual text/non-text stroke classification in online handwritten notes with conditional random fields[J].Pattern Recognition,2014,47(3):959-968.
    [10]
    Malakar S,Das R K,Sarkar R,et al.Handwritten and printed word identification using gray-scale feature vector and decision tree classifier[J].Procedia Technology,2013,10:831-839.
    [11]
    Song Y H,Xiao G L,Zhang Y L,et al.A handwritten character extraction algorithm for multi-language document image[C]∥Proceedings of 11th International Conference on Document Analysis and Recognition (ICDAR).Piscataway,NJ:IEEE Press,2011:93-98.
    [12]
    Rani R,Dhir R,Lehal G S.Script identification of pre-segmented multi-font characters and digits[C]∥Proceedings of 12th International Conference on Document Analysis and Recognition (ICDAR).Piscataway,NJ:IEEE Press,2013:1150-1154.
    [13]
    付强,丁晓青,蒋焰.基于多信息融合的中文手写地址字符串切分与识别[J].电子与信息学报,2008,30(12):2916-2920.Fu Q,Ding X Q,Jiang Y.Segmentation and recognition algorithm for Chinese handwritten address character string[J].Journal of Electronics & Information Technology,2008,30(12):2916-2920(in Chinese).
    [14]
    Blagojevic R,Chang S H H,Plimmer B.The power of automatic feature selection:Rubine on steroids[C]∥Proceedings of the Seventh Sketch-Based Interfaces and Modeling Symposium (SBIM).Goslar:Eurographics Association,2010:79-86.
    [15]
    Paulson B,Hammond T.PaleoSketch:Accurate primitive sketch recognition and beautification[C]∥Proceedings of 13th International Conference on Intelligent User Interfaces (IUI2008).New York:ACM,2008:1-10.
    [16]
    Paulson B.Rethinking pen input interaction:Enabling freehand sketching through improved primitive recognition[D].State of Texas:Texas A&M University,2010.
    [17]
    胡正平,冯凯.高维空间多分辨率最小生成树模型的自适应一类分类算法[J].自动化学报,2012,38(5):769-775.Hu Z P,Feng K.An adaptive one-class classification algorithm based on multi-resolution minimum spanning tree model in high-dimensional space[J].Acta Automatic Sinica,2012,38(5):769-775(in Chinese).
    [18]
    谢毓湘,栾悉道,陈丹雯,等.一种基于局部不变特征的图像特定场景检测方法[J].国防科技大学学报,2013,35(6):78-83.Xie Y X,Luan X D,Chen D W,et al.A method of specific image scene detection based on local invariant features[J].Journal of National University of Defense Technology,2013,35(3):78-83(in Chinese).
    [19]
    Liu C L,Hao H W,Sako H.Confidence transformation for combining classifiers[J].Pattern Analysis and Applications,2004,7(1):2-17.
    [20]
    Liu C L.Classifier combination based on confidence transformation[J].Pattern Recognition,2005,38(1):11-28.
    [21]
    Costagliola G,de Rosa M,Fuccella V.Recognition and autocompletion of partially drawn symbols by using polar histograms as spatial relation descriptors[J].Computers & Graphics,2014,39(2):101-116.
    • Relative Articles
    • Supplements(0)
    • Cited By
  • 加载中

Catalog

    通讯作者: 陈斌, bchen63@163.com
    • 1. 

      沈阳化工大学材料科学与工程学院 沈阳 110142

    1. 本站搜索
    2. 百度学术搜索
    3. 万方数据库搜索
    4. CNKI搜索
    Get Citation
    PDF
    XML

    Article Metrics

    Article views(886) PDF downloads(389) Cited by()
    Proportional views
    Related

    Copyright © Journal of Beijing University of Aeronautics and Astronautics

    Address: Editorial Department of Journal of Beijing University of Aeronautics and Astronautics, 37 Xueyuan Road, Haidian District, Beijing Post Code: 100191 Email: jbuaa@buaa.edu.cn

    Supported by: Beijing Renhe Information Technology Co., Ltd.    

    /

    DownLoad:  Full-Size Img  PowerPoint
    Return
    Return