Detection of Buried Roman Wall Remains in Ground-penetrating Radar Data using Template Matching

被引:12
作者
Verdonck, Lieven [1 ]
机构
[1] Univ Ghent, Dept Archaeol, Sint Pietersnieuwstr 35, B-9000 Ghent, Belgium
关键词
Archaeological geophysics; ground-penetrating radar; feature extraction; template matching; archaeological interpretation; Roman villa; HIGH-RESOLUTION GPR; ARCHAEOLOGICAL FEATURES; 3D GPR; EXTRACTION; VISUALIZATION; ATTRIBUTES; SITE; DISCOVERY; TREES;
D O I
10.1002/arp.1540
中图分类号
K85 [文物考古];
学科分类号
0601 ;
摘要
Whereas in the last decades the acquisition and processing of archaeological ground-penetrating radar (GPR) data have become mature, the interpretation is still challenging. Manual delineation in three dimensions is time consuming, and often the determination of an isosurface value is not straightforward. This paper presents a method designed specifically for the extraction of buried linear features such as wall foundations, based on template matching. First, the three-dimensional (3D) GPR data cube is synthesized into a two-dimensional (2D) slice. To achieve this, an energy slice based on a sufficiently large time window may often be appropriate, although in this study a combination with other attributes, for example based on phase symmetry, made weak anomalies more distinct. In the next step, we compute the 2D normalized cross-correlation of the composite 2D slice and a number of templates with dimensions similar to the walls in the data set. Of the resulting correlation matrices, the highest correlation coefficient is kept for each pixel, if it exceeds a certain threshold. In this way, wall foundations are successfully mapped, but also many false detections are produced. The latter are greatly reduced in number by using a size threshold and discarding isolated features. The remaining regions are enclosed in bounding boxes, which after vertical extrusion can be used as a simplified 3D representation of the wall structures, and for the creation of a filtered isosurface. For the evaluation of our results, a manual interpretation was used. In the 2D case (i.e. when comparing the total area of the automatically mapped structures versus the manually delineated ones), both the detection rate and the correctness were similar to 77%. Slightly lower rates (similar to 71%) were obtained in the 3D case (i.e. comparing volumes). Our method was applied to the GPR survey of a Roman villa in Kent, UK. Copyright (C) 2016 John Wiley & Sons, Ltd.
引用
收藏
页码:257 / 272
页数:16
相关论文
共 50 条
[31]   Stepped-frequency ground-penetrating radar for detection of small non-metallic buried objects [J].
Jakobsen, KB ;
Sorensen, HBD ;
Nymann, O .
DETECTION AND REMEDIATION TECHNOLOGIES FOR MINES AND MINELIKE TARGETS II, 1997, 3079 :538-542
[32]   Tree trunk cavity detection using ground-penetrating radar migration imaging [J].
Li G. ;
Liu M. ;
Xu H. ;
Zhang Y. .
Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 2021, 37 (15) :154-160
[33]   Efficient detection of mains water leaks using ground-penetrating radar (GPR) [J].
Charlton, M ;
Mulligan, M .
SUBSURFACE AND SURFACE SENSING TECHNOLOGIES AND APPLICATIONS III, 2001, 4491 :375-386
[34]   Pavement-distress detection using ground-penetrating radar and network in networks [J].
Tong, Zheng ;
Yuan, Dongdong ;
Gao, Jie ;
Wei, Yongfeng ;
Dou, Hui .
CONSTRUCTION AND BUILDING MATERIALS, 2020, 233 (233)
[35]   High-resolution Ground-Penetrating Radar Imaging of Buried Culture Heritage [J].
Zhao, Wenke ;
Tian, Gang ;
Pipan, Michele ;
Forte, Emanuele ;
Wang, Yimin ;
Li, Xuejing .
NEAR-SURFACE GEOPHYSICS AND GEOHAZARDS, 2014, :483-487
[36]   Efficient multiple layer boundary detection in ground-penetrating radar data using an extended Viterbi algorithm [J].
Smock, Brandon ;
Wilson, Joseph .
DETECTION AND SENSING OF MINES, EXPLOSIVE OBJECTS, AND OBSCURED TARGETS XVII, 2012, 8357
[37]   Buried object characterization via ground-penetrating radar and Huynen polarimetric parameters [J].
Sadjadi, FA ;
Chun, CSL ;
Sullivan, A ;
Gaunaurd, GC .
OPTICAL ENGINEERING, 2005, 44 (12)
[38]   Real-time object detection using power spectral density of ground-penetrating radar data [J].
Saghafi, Abolfazl ;
Jazayeri, Sajad ;
Esmaeili, Sanaz ;
Tsokos, Chris P. .
STRUCTURAL CONTROL & HEALTH MONITORING, 2019, 26 (06)
[39]   Contextual Learning in Ground-Penetrating Radar Data Using Dirichlet Process Priors [J].
Ratto, Christopher R. ;
Morton, Kenneth D., Jr. ;
Collins, Leslie M. ;
Torrione, Peter A. .
DETECTION AND SENSING OF MINES, EXPLOSIVE OBJECTS, AND OBSCURED TARGETS XVI, 2011, 8017
[40]   Improving ground-penetrating radar data in sedimentary rocks using deterministic deconvolution [J].
Xia, JH ;
Franseen, EK ;
Miller, RD ;
Weis, TV ;
Byrnes, AP .
JOURNAL OF APPLIED GEOPHYSICS, 2003, 54 (1-2) :15-33