基于改进主动轮廓模型的无人机影像矿区地裂缝提取  

Ground Fissure Extraction Method based on Improved Active Contour Model for UAV Images in Mining Areas

作　　者：郝明[1,2] 林惠晶 高彦彦 HAO Ming;LIN Huijing;GAO Yanyan(Jiangsu Key Laboratory of Resources and Environmental Information Engineering,China University of Mining and Technology,Xuzhou 221116,China;School of Environment and Spatial Informatics,China University of Mining and Technology,Xuzhou 221116,China;Piesat Information Technology Company Limited,Wuhan 430010,China)

机构地区：[1]中国矿业大学江苏省资源环境信息工程重点实验室,徐州221116 [2]中国矿业大学环境与测绘学院,徐州221116 [3]航天宏图信息技术股份有限公司,武汉430010

出　　处：《地球信息科学学报》2022年第12期2448-2457,共10页Journal of Geo-information Science

基　　金：中央高校基本科研业务费专项资金(2021YCPY0113);国家自然科学基金项目(42271368、41701504)。

摘　　要：矿区地裂缝精准识别对防灾、减灾和生态环境修复具有重要意义。针对高分辨率无人机影像较难自动精确提取地裂缝的问题,本文提出了一种基于改进主动轮廓模型的无人机影像矿区地裂缝提取方法。首先,采用Otsu算法计算背景和地裂缝初值作为先验知识;其次,构建背景和地裂缝初值的提取能量函数,并引入到传统CV主动轮廓模型,增强地裂缝提取的针对性;最后,通过轮廓的不断演化实现地裂缝的提取。以内蒙古扎赉诺尔矿区为研究区、无人机影像为数据源,采用改进主动轮廓模型方法进行地裂缝提取,并与传统的Canny边缘检测算法、支持向量机(SVM)、最大似然(MLM)和传统CV主动轮廓模型方法进行对比分析。结果表明:在地物类型较为单一的小范围区域,传统的Canny边缘检测算法和传统CV主动轮廓模型提取效果较差,改进主动轮廓模型、SVM和MLM共3种方法均可以取得较好的效果,其中,改进主动轮廓模型方法精度最高;在地物类型相对复杂的大范围区域,传统的Canny边缘检测算法、SVM、MLM和传统CV主动轮廓模型方法存在较多的漏提和误提,Kappa系数均低于0.7,而本文改进主动轮廓方法依然可以取得较好的效果,Kappa系数达到0.9左右。因此,本文提出的方法通过引入先验知识可有效提高地裂缝提取的精度和稳定性。Accurate identification of ground fissures in mining areas is significant for disaster prevention,mitigation, and ecological environment restoration. In this study, a ground fissure extraction method is proposed based on the improved active contour model for UAV images in mining areas, aiming at accurately extracting ground fissures from high-resolution UAV images. Firstly, the Otsu algorithm was used to calculate the background and initial values of ground fissures as prior knowledge. Secondly, the extraction energy functions of the background and initial values of ground fissures were constructed and introduced into the traditional CV active contour model to enhance the pertinence of ground fissures extraction. Finally, ground fissures were extracted through the continuous evolution of the contour. Based on UAV images obtained in Dalai Nurg mining area, Inner Mongolia, the improved active contour model was used to extract ground fractures, and compared with traditional Canny edge detection algorithm, Support Vector Machine(SVM), Maximum Likelihood Method(MLM), and traditional CV active contour model methods for analysis and accuracy evaluation. The results show that the traditional Canny edge detection algorithm and traditional CV active contour model had the poor extraction in a small area with a single type of land cover. The improved active contour model, SVM, and MLM had achieved good results, and the improved active contour model method had the highest accuracy. In addition,in a large area with relatively complex land cover types, the traditional methods such as Canny edge detection algorithm, SVM, MLM, and CV active contour model had many omissions and errors, and the kappa coefficient was lower than 0.7. However, the improved active contour method still achieved better results, and the Kappa coefficient was about 0.9. Therefore, the proposed method could effectively improve the accuracy and stability of ground fissure extraction by introducing prior knowledge.

关 键 词：地裂缝 OTSU算法 先验知识 主动轮廓模型 无人机影像 矿区 地物类型 稳定性 

分 类 号：TP391.41[自动化与计算机技术—计算机应用技术] TD17[自动化与计算机技术—计算机科学与技术]