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

doi:10.13474/j.cnki.11-2246.2024.0225

Bulletin of Surveying and Mapping ›› 2024, Vol. 0 ›› Issue (2): 140-143.doi: 10.13474/j.cnki.11-2246.2024.0225

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

ZHANG Mengyuan¹, ZHAO Junhua², SUN Yumei^1,3, HAO Zongpeng⁴

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

Abstract

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

CLC Number:

P237

ZHANG Mengyuan, ZHAO Junhua, SUN Yumei, HAO Zongpeng. Identification of construction waste information with multiple features using object-oriented morphological operation[J]. Bulletin of Surveying and Mapping, 2024, 0(2): 140-143.

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

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