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
  • [1] Template-matching based detection of hyperbolas in ground-penetrating radargrams for buried utilities
    Sagnard, Florence
    Tarel, Jean-Philippe
    JOURNAL OF GEOPHYSICS AND ENGINEERING, 2016, 13 (04) : 491 - 504
  • [2] Automatic detection of mud-wall signatures in ground-penetrating radar data
    Bordon, Pablo
    Martinelli, Patricia
    Zabala Medina, Peter
    Bonomo, Nestor
    Ratto, Norma Rosa
    ARCHAEOLOGICAL PROSPECTION, 2021, 28 (01) : 89 - 106
  • [3] Estimating geometrical parameters of cylindrical targets detected by ground-penetrating radar using template matching algorithm
    Reza Ahmadi
    Nader Fathianpour
    Arabian Journal of Geosciences, 2017, 10
  • [5] Automatic detection of hyperbolic signatures in ground-penetrating radar data
    Al-Nuaimy, W
    Huang, Y
    Eriksen, A
    Nguyen, VT
    SUBSURFACE AND SURFACE SENSING TECHNOLOGIES AND APPLICATIONS III, 2001, 4491 : 327 - 335
  • [6] A study of the effect of buried biomass on ground-penetrating radar performance
    Niltawach, N
    Chen, CC
    Johnson, JT
    Baertlein, BA
    PASSIVE MILLIMETER-WAVE IMAGING TECHNOLOGY VI AND RADAR SENSOR TECHNOLOGY VII, 2003, 5077 : 133 - 144
  • [7] Experimental Detection of Buried Sub-mm Diameter Wires Using Microwave Ground-Penetrating Radar
    Wagner, Samuel
    Pancrazio, Stephen
    Hossain, Ababil
    Anh-Vu Pham
    2021 IEEE USNC-URSI RADIO SCIENCE MEETING (JOINT WITH AP-S SYMPOSIUM), 2021, : 37 - 38
  • [8] Crevasses detection in Himalayan glaciers using ground-penetrating radar
    Singh, K. K.
    Negi, H. S.
    Ganju, A.
    Kulkarni, A. V.
    Kumar, A.
    Mishra, V. D.
    Kumar, S.
    CURRENT SCIENCE, 2013, 105 (09): : 1288 - 1295
  • [9] Modeling of crosshole ground-penetrating radar data
    Balkaya, Caglayan
    Gokturkler, Gokhan
    PAMUKKALE UNIVERSITY JOURNAL OF ENGINEERING SCIENCES-PAMUKKALE UNIVERSITESI MUHENDISLIK BILIMLERI DERGISI, 2016, 22 (06): : 581 - 596
  • [10] Improving Buried Threat Detection in Ground-Penetrating Radar with Transfer Learning and Metadata Analysis
    Colwell, Kenneth A.
    Torrione, Peter A.
    Morton, Kenneth D., Jr.
    Collins, Leslie M.
    DETECTION AND SENSING OF MINES, EXPLOSIVE OBJECTS, AND OBSCURED TARGETS XX, 2015, 9454