测绘通报 ›› 2024, Vol. 0 ›› Issue (2): 140-143.doi: 10.13474/j.cnki.11-2246.2024.0225

• 技术交流 • 上一篇    下一篇

利用形态学算法进行面向对象的建筑垃圾多特征遥感识别

张梦媛1, 赵军华2, 孙玉梅1,3, 郝宗朋4   

  1. 1. 石家庄铁路职业技术学院, 河北 石家庄 050000;
    2. 石家庄铁道大学, 河北 石家庄 050000;
    3. 河北省桥隧工程施工智能控制技术创新中心, 河北 石家庄 050000;
    4. 中铁四局集团第三 建设有限公司, 天津 300000
  • 收稿日期:2023-06-10 出版日期:2024-02-25 发布日期:2024-03-12
  • 通讯作者: 赵军华。E-mail:zhaojh@stdu.edu.cn
  • 作者简介:张梦媛(1995—),女,硕士,助教,主要研究方向为高分辨率遥感影像识别。E-mail:zhangmyhzp@163.com

Identification of construction waste information with multiple features using object-oriented morphological operation

ZHANG Mengyuan1, ZHAO Junhua2, SUN Yumei1,3, HAO Zongpeng4   

  1. 1. Shijiazhuang Institute of Railway Technology, Shijiazhuang 050000, China;
    2. Shijiazhuang Tiedao University, Shijiazhuang 050000, China;
    3. Hebei Province Bridge and Tunnel Engineering Construction Intelligent Control Technology Innovation Center, Shijiazhuang 050000, China;
    4. The Third Construction Co., Ltd., of CTCE Group, Tianjin 300000, China
  • Received:2023-06-10 Online:2024-02-25 Published:2024-03-12

摘要: 建筑垃圾的长期堆积和不科学管理,将引发各种生态和社会问题,进而严重影响城市的绿色可持续发展。在固体废弃物信息识别研究中,因未顾及建筑物与建筑垃圾之间纹理特征的差异,在分类过程中会出现两者混淆现象。针对此问题,数学形态学算法能够突出建筑垃圾灰度强度特征,进而结合各类地物在形态、光谱、几何和纹理等特征差异,实现面向对象多特征的建筑垃圾信息提取。以北京房山区保合庄为例,采用WorldView-2遥感影像开展研究,通过建立混淆矩阵和可分离性评价指标,对建筑垃圾识别结果进行精度评估,总体精度OA达到96.6%,可准确分离建筑垃圾与建筑物,两者分离性为1.000,结果表明该方法能够有效解决建筑垃圾与建筑物混淆问题,在建筑垃圾信息提取方面具有可靠的适用性。

关键词: 建筑垃圾, 多特征, 信息识别, 数学形态学

Abstract: The long-term storage and unscientific management of construction waste will cause various ecological and social problems, which will seriously affect the green and sustainable development of the city. In the research of solid waste information recognition, the difference of texture characteristics between buildings and construction waste is not considered, which may lead to confusion between them in the classification process. To solve this problem, mathematical morphology algorithm can be used to highlight the gray intensity characteristics of construction waste. Then the differences of morphological, spectral, geometric and texture characteristics of various ground objects are analyzed to realize object-oriented construction waste information extraction with multiple features. Taking Baohezhuang Village, Fangshan District, Beijing as an example, the experiment is conducted using WorldView-2 remote sensing image. The accuracy of construction waste extraction is evaluated by establishing confusion matrix and separability evaluation index. The overall accuracy is up to 96.6%, and the separation between construction waste and buildings is up to 1.000. The results show that this method can effectively solve the confusion problem between construction waste and buildings, and has reliable applicability in the information extraction of construction waste.

Key words: construction waste, multiple features, information recognition, mathematical morphology

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