北京航空航天大学学报 ›› 2019, Vol. 45 ›› Issue (12): 2523-2532.doi: 10.13700/j.bh.1001-5965.2019.0376

• 论文 • 上一篇    下一篇

结合轮廓及骨架序列编码的二维形状识别

卢勇强, 栗志扬, 陈祎楠, 刘朝斌, 黄一鸣   

  1. 大连海事大学 信息科学技术学院, 大连 116026
  • 收稿日期:2017-07-09 出版日期:2019-12-20 发布日期:2019-12-31
  • 通讯作者: 栗志扬 E-mail:lizy0205@gmail.com
  • 作者简介:卢勇强 男,硕士研究生。主要研究方向:计算机视觉、图像处理;栗志扬 男,博士,副教授,硕士生导师。主要研究方向:计算机视觉、云计算与大数据;陈祎楠 男,硕士研究生。主要研究方向:计算机视觉;刘朝斌 男,博士,教授,博士生导师。主要研究方向:云计算与云安全;黄一鸣 男,硕士研究生。主要研究方向:图像处理、组合优化。
  • 基金资助:
    国家自然科学基金(61300187,61672379);辽宁省自然科学基金(2019-MS-028)

Two-dimensional shape recognition based on contour and skeleton sequence coding

LU Yongqiang, LI Zhiyang, CHEN Yinan, LIU Zhaobin, HUANG Yiming   

  1. School of Information Science and Technology, Dalian Maritime University, Dalian 116026, China
  • Received:2017-07-09 Online:2019-12-20 Published:2019-12-31
  • Supported by:
    National Natural Science Foundation of China (61300187,61672379); Liaoning Provincial Natural Science Foundation of China (2019-MS-028)

摘要: 二维形状识别是物体识别中的一个基本问题,被广泛地应用于商标检索、指纹识别、物体定位、图像检索等多个领域。其中,基于生物信息学的二维形状识别是近期一个新的研究方向,基本思想是把二维形状的轮廓转化为生物信息序列,借助标准的生物信息序列分析工具来进行二维形状的匹配和识别。不过,利用轮廓进行信息序列编码存在编码冗余和编码准确性不高的问题,本文提出了一种新型的结合形状轮廓和骨架的序列编码方法。该方法利用骨架表示形状的细长分支,减少编码的冗余;并分别对轮廓和骨架进行不同类型的编码,具备编码简洁、后续匹配准确性高等优点。最后,本文在三个公开数据集上进行大量的形状识别实验,并与多种通用形状识别方法进行了比较。实验表明,本文方法在多个实验中均取得了较高的识别准确率,相比基本的形状特征描述方法,准确率提高了近5%。

关键词: 形状匹配, 轮廓特征, 骨架特征, 特征描述子, 生物信息序列

Abstract: Two-dimensional shape recognition is a fundamental problem in object recognition, which is widely used in trademark retrieval, fingerprint recognition, object location, image retrieval and other fields. Recently, two-dimensional shape recognition based on bioinformatics has become a new research direction, whose basic idea is to transform the contour of a planar shape into a biological information sequence. The two-dimensional shape matching and recognition are then achieved by the standard alignment tools of such biological information sequence. However, the classic coding method still suffers from the problems of code redundancy and low accuracy. In this paper, we present a new coding method based on both the shape contour and skeleton sequence. Firstly, skeletons are used to represent slender branches of the shape to reduce coding redundancy. Secondly, the contour and skeleton are coded in different ways to compact the code and improve the matching accuracy. Finally, extensive shape recognition experiments are conducted on three public datasets and the proposed method is compared with a variety of shape recognition methods. The experimental results demonstrate that the proposed method has achieved higher performance in several experiments, and the recognition accuracy rate is improved by nearly 5% compared with basic shape feature description methods.

Key words: shape matching, contour features, skeleton features, feature descriptors, biological information sequences

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