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刘锋,王斌.目标边界点集的层次化描述及其在形状检索中的应用.软件学报,0,(0):0
目标边界点集的层次化描述及其在形状检索中的应用
Hierarchical Point-set Description of Object Edge and its Application in Shape Retrieval
投稿时间:2017-09-26  修订日期:2017-10-26
DOI:10.13328/j.cnki.jos.005535
中文关键词:  图像分析|边界点集|层次化描述|形状检索
英文关键词:image analysis|edge point-set|hierarchical description|shape retrieval
基金项目:国家重点研发计划项目(2017YFD0700501);国家自然科学基金项目(61372158);江苏省科技计划(产学研合作前瞻性联合研究)(BY2016009-03);江苏省高校优秀科技创新团队项目(2017-15);江苏高校优势学科建设工程资助项目(PAPD)
作者单位E-mail
刘锋 南京财经大学信息工程学院, 江苏南京 210023  
王斌 南京财经大学信息工程学院, 江苏南京 210023
南京财经大学电子商务省级重点实验室, 江苏南京 210023 
wangbin@njue.edu.cn 
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中文摘要:
      本文提出了一种能一般的用于轮廓线形状和区域形状图像检索的形状描述方法.该方法将目标形状的边界(包括内边界)表示为一个无序的点集,沿各方向对点集的迭代分割,建立一个层次化的边界点集描述模型,通过对各层形状边界的分割比和分散度的几何特征度量,产生各层的形状特征描述,对它们进行组合,建立一个对目标形状的层次化描述.两个目标形状的差异性度量定义为它们的层次化描述子的L-1距离.该方法具有:(1)通用性,能描述轮廓线形状和区域形状这两种不同类型的形状.(2)可扩展性,基于本文提出的分层描述框架,可以将分割比和分散度这两种几何度量进行扩展,纳入更多其他几何特征度量,以进一步提高形状描述的精度.(3)多尺度描述特性,本文提出的分层的描述机制使得描述子具有内在的由粗到细的形状表征能力.(4)较低的计算复杂性,由于仅仅计算目标图像的边界像素点,使得算法具有较高的计算效率.用MPEG-7 CE-2区域形状图像库和MPEG-7 CE-1轮廓线形状图像库这两个标准测试集对该方法进行评估,并与同类的其他形状描述方法进行比较,实验结果表明本文提出的方法在综合考虑检索精确率、检索效率和一般应用能力等指标的情况下,其性能上要优于各种参与比较的方法.
英文摘要:
      A novel shape description which can be generally applied to both contour shape and region shape recognition is proposed in this paper. This method treats the edge (including the inner edge) of the object as an unordered point-set, a hierarchical description model is built by iteratively partitioning the edge of the object into progressively smaller parts along different directions. At each level of the hierarchy structure, the geometrical features of the object edge are characterized by two measurements, partition ratio and dispersion degree. Combining them, a hierarchical description of the object shape can then be constructed. The dissimilarity of two shapes can be measured by computing the L-1 distance between their hierarchical shape descriptors. The merits of the proposed method can be summarized as follows:(1) Both contour shape and region shape can be effectively described by this method, thus it has the ability for general use. (2) Based on the proposed hierarchical description framework, besides the proposed two measures, partition ratio and dispersion degree, many other measures can be included for meeting various accuracy requirements on shape recognition, so the proposed method has extendibility. (3) The proposed hierarchical description scheme make the available descriptors characterize the shape from coarse to fine, so the proposed descriptor is multi-scale. (4) Instead of using all the pixel points of the object, the proposed method only take the edge points of the object into account, for this reason, it has a relative low computational complexity. Two standard test sets including MPEG-7 CE-2 region shape database and MPEG-7 CE-1 contour shape database are used to evaluate the performance of the proposed method. The experimental results indicate that the proposed method outperforms the state-of-the-art approaches in terms of a comprehensive consideration on the retrieval rates, retrieval efficiency and general application ability.
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