基于无人机图像比对的违章建筑检测方法
An Illegal Building Detection Method Based on UAV Image Comparison
魏松林 1林静敏 2李伟权 1唐凯3
作者信息
- 1. 厦门海洋职业技术学院 信息工程学院,福建 厦门 361100
- 2. 厦门城市职业学院 人工智能学院,福建 厦门 361008
- 3. 集美大学 海洋信息工程学院,福建 厦门 361021;厦门唯识筋斗云科技有限公司,福建 厦门 361115
- 折叠
摘要
针对当前违章建筑图像识别和图像变化检测中存在的误检、漏检等问题,提出了一套基于无人机图像比对的违章建筑检测方法,创新性地采用YCrCb颜色空间三分量分别进行差分运算和阈值化处理,结合图像分类算法排除非施工活动引起的图像变化,通过结构相似性检测,对新旧时相变化区域相似度进行评估,识别出在建违章建筑引起的图像变化区域.与目前主流的基于无人机图像的非单一类型违章建筑物检测方法相比,4032×3024 分辨率图像的检测时间缩短 40.9%至 4.08 s,正确率提高 15.3%达到 86.3%且无漏检测.结果表明,本方法可有效、快速识别在建违章建筑区域,有利于城市管理人员及时发现并处理这些违章行为,从而提高城市管理的效率和响应速度.
Abstract
In response to the problems of false positives and false negatives in the current illegal building image recognition and image change detection,this paper proposes a method for detecting illegal building using UAV(Unmanned Aerial Vehicle)images,innovatively using the YCrCb color space to perform differential operations and thresholding on the three components separately,and combining image classification algorithms to exclude image changes caused by non-construction activities.Finally,by using structural similarity detection to evaluate the similarity of image change regions in new and old-time phases,the method identifies the image change regions caused by illegal building.Compared with the current mainstream non-single type violation building detection methods based on drone images,the detection time of 4032×3024 resolution image is reduced by 40.9%to 4.08 seconds,and the accuracy is improved by 15.3%to reach 86.3%,with no missed detections.The results show that this method can effectively and quickly identify areas where illegal building is underway,which is beneficial for city managers to discover and handle these illegal activities in a timely manner,thus improving the efficiency and response speed of urban management.
关键词
违章建筑检测/无人机图像比对/YCrCb颜色空间/分类过滤Key words
illegal building detection/UAV image comparison/YCrCb color space/classification filtering引用本文复制引用
出版年
2024
NETL
NSTL
万方数据