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:2019,28(1):140-146
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复杂场景下在建建筑区域识别方法
(1.四川大学 电子信息学院, 成都 610065;2.东莞前沿技术研究院, 东莞 523000)
Recognizing Building Areas under Construction in Complex Scenarios
(1.College of Electronics and Information Engineering, Sichuan University, Chengdu 610065, China;2.Dongguan Institute of Advanced Technology, Dongguan 523000, China)
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投稿时间:2018-06-13    修订日期:2018-07-04
中文摘要: 针对在建建筑区域具有与周围非在建建筑颜色特征不同、与周围自然环境纹理特征不同的特点,提出了一种基于在建建筑颜色和纹理特征的高空影像中在建建筑区域识别方法.首先对只包含在建建筑图像数据集中的图像进行颜色和纹理特征提取,由这些特征矢量构建图像特征索引库;然后将待检测图像分块,对其颜色聚类屏蔽绿色植被区域并计算特征矢量,将其与特征索引库做相似性度量,判定该图像块在整个待检测图中的位置,对检测到的在建建筑用红色矩形框和唯一的标识符框选出来.实验结果显示,利用本文提出的在建建筑区域识别方法,能够有效地识别城市高空影像中的在建建筑区域,基于本文算法的系统可以运用于城市规划.
Abstract:In view of the fact that the building area under construction has features that are different from the features of the surrounding non-construction buildings and different from the surrounding natural environment texture features, a construction area recognition method based on the color and texture features of the building under construction is proposed. Firstly, color and texture features are extracted from images that only contain the image data of the building under construction. The image feature index database is constructed from these feature vectors. Then, the image to be detected is divided into blocks, and the color vegetation is masked to the green vegetation area and the feature vector is calculated. It is measured by the similarity with the feature index database, to determine the position of the image block in the entire detected image, and to select the red rectangle and the unique identifier box for the detected building under construction. The experimental results show that the proposed method for recognizing the building area under construction can effectively identify the building area under construction in urban images from high altitude. The system based on this algorithm can be applied to urban planning.
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基金项目:四川省教育厅科研项目(18ZB0355)
引用文本:
周文一,何小海,卿粼波,万园洁,郑新波.复杂场景下在建建筑区域识别方法.计算机系统应用,2019,28(1):140-146
ZHOU Wen-Yi,HE Xiao-Hai,QING Lin-Bo,WAN Yuan-Jie,ZHENG Xin-Bo.Recognizing Building Areas under Construction in Complex Scenarios.COMPUTER SYSTEMS APPLICATIONS,2019,28(1):140-146

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