Automatic citrus tree extraction from UAV images and digital surface models using circular Hough transform

Computers and Electronics in Agriculture

Volumn 150, Issue , 2018, Pages 289-301

  Koc San, Dilek ^a   Selim, Serdar ^a   Aslan, Nagihan ^a   San, Bekir Taner ^a  

^a AKDENIZ UNIVERSITY   (Turkey)

Author keywords

Circular Hough transform; Citrus tree; Tree extraction; UAV

Indexed keywords

ANTENNAS; EDGE DETECTION; EXTRACTION; FEATURE EXTRACTION; FORESTRY; HOUGH TRANSFORMS; IMAGE PROCESSING; STATISTICAL TESTS; TREES (MATHEMATICS); UNMANNED AERIAL VEHICLES (UAV);

AERIAL VEHICLE; AUTOMATIC EXTRACTION; CIRCULAR HOUGH TRANSFORMS; CITRUS TREE; DATA SET; DIGITAL SURFACE MODELS; IMAGE SURFACE; TREE EXTRACTION; UNMANNED AERIAL VEHICLE; VEHICLE IMAGES;

LOCATION;

ACCURACY ASSESSMENT; AIRBORNE SENSOR; ALGORITHM; CROP YIELD; DATA SET; DETECTION METHOD; FRUIT; MULTISPECTRAL IMAGE; NUMERICAL MODEL; SATELLITE DATA; SATELLITE IMAGERY; TREE;

CITRUS;

EID: 85046807065     PISSN: 01681699     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.compag.2018.05.001     Document Type: Article

References (82)

1. Agüera, F., Liu, J.G., Automatic greenhouse delineation from QuickBird and Ikonos satellite images. Comput. Electron. Agric. 66:2 (2009), 191–200, 10.1016/j.compag.2009.02.001.
2. Aliero, M.M., Mukhtar, N.R.B., Al-Doksi, J., 2014. The Usefulness of Unmanned Airborne Vehicle (UAV) Imagery for Automated Palm Oil Tree Counting, J. Forest., Researchjournali, India.
3. Alonzo, M., Bookhagen, B., Roberts, D.A., Urban tree species mapping using hyperspectral and lidar data fusion. Remote Sens. Environ. 148 (2014), 70–83, 10.1016/j.rse.2014.03.018.
4. Ardila, J.P., Bijker, W., Tolpekin, V.A., Stein, A., Multitemporal change detection of urban trees using localized region - based active contours in VHR images. Remote Sens. Environ. 124 (2012), 413–426, 10.1016/j.rse.2012.05.027.
5. Ardila, J.P., Bijker, W., Tolpekin, V.A., Stein, A., Context-sensitive extraction of tree crown objects in urban areas using VHR satellite images. Int. J. Appl. Earth Obs. Geoinf. 15 (2012), 57–69, 10.1016/j.jag.2011.06.005.
6. Basalamah, S., Histogram based circle detection. IJCSNS Int. J. Comput. Sci. Network Security 12:8 (2012), 40–43.
7. Bazi, Y., Malek, S., Alajlan, N., AlHichri, H., An Automatic Approach for Palm Tree Counting in UAV Images. 2014, IEEE Geoscience and Remote Sensing Symposium, IEEE, Quebec City, Canada, 537–540.
8. Canny, J., Computational approach to edge detection. IEEE Trans. Pattern Anal. Mach. Intell. 8 (1986), 679–698.
9. Chmielewski L.J., Bator M., Zasada M., Stereńczak K., Strzeliński P. 2010. Fuzzy Hough Transform-Based Methods for Extraction and Measurements of Single Trees in Large-Volume 3D Terrestrial LIDAR Data. In: Bolc, L., Tadeusiewicz, R., Chmielewski, L.J., Wojciechowski, K. (Eds). Computer Vision and Graphics. ICCVG 2010. Lecture Notes in Computer Science, vol. 6374. Springer, Berlin, Heidelberg.
10. Colomina, I., Molina, P., Unmanned aerial systems for photogrammetry and remote sensing: A review. ISPRS J. Photogramm. Remote Sens. 92 (2014), 79–97, 10.1016/j.isprsjprs.2014.02.013.
11. Croitoru, A., Doytsher, Y., Right-angle rooftop polygon extraction in regularized urban areas: cutting the corners. Photogramm. Rec. 19 (2004), 311–341.
12. Cross, A.M., Detection of circular geological features using the Hough transform. Int. J. Remote Sens. 9:9 (1988), 1519–1528, 10.1080/01431168808954956.
13. Cui, S., Yan, Q., Reinartz, P., Complex building description and extraction based on Hough transformation and cycle detection. Remote Sensing Letters 3:2 (2012), 151–159, 10.1080/01431161.2010.548410.
14. Culvenor, D.S., TIDA: an algorithm for the delineation of tree crowns in high spatial resolution remotely sensed imagery. Comput. Geosci. 28:2002 (2002), 33–44.
15. Dalponte, M., Qrka, H.O., Ene, L.T., Gobakken, T., Naesset, E., Tree crown delineation and tree species classification in boreal forests using hyperspectral and ALS data. Remote Sens. Environ. 140 (2014), 306–317, 10.1016/j.rse.2013.09.006.
16. Demir, N. 2017. Using UAVs for detection of trees from digital surface models. J. Forest. Res. 1–9. (Accepted). doi: 10.1007/s11676-017-0473-9.
17. Diaz-Varela, R.A., Rosa, R., Leon, L., Zarco-Tejada, P.J., High-resolution airborne UAV imagery to assess olive tree crown parameters using 3D photo reconstruction: application in breeding trials. Remote Sens. 7:4 (2015), 4213–4232, 10.3390/rs70404213.
18. Duda, R.O., Hart, P.E., Use of Hough transformation to detect lines and curve in pictures. Commun. ACM 15:1 (1972), 11–15, 10.1145/361237.361242.
19. ECCM, 2011. Citrus Orchard Technical Specification for Trees of hope project. Edinburgh Centre for Carbon Management (ECCM), Clinton Hunter Development Initiative (CHDI) in Malawi. 28p.
20. Ene, L., Naesset, E., Gobakken, T., Single tree detection in heterogeneous boreal forests using airborne laser scanning and area-based stem number estimates. Int. J. Remote Sens. 33:16 (2012), 5171–5193, 10.1080/01431161.2012.657363.
21. Erikson, M., Species classification of individually segmented tree crowns in high-resolution aerial images using radiometric and morphologic image measures. Remote Sens. Environ. 91:2004 (2004), 469–477, 10.1016/j.rse.2004.04.006.
22. Erikson, M., Olofsson, K., Comparison of three individual tree crown detection methods. Mach. Vis. Appl. 16:4 (2005), 258–265, 10.1007/s00138-005-0180-y.
23. Gougeon, F.A., A crown-following approach to the automatic delineation of individual tree crowns in high-spatial resolution aerial images. Canadian J. Remote Sens. 21:3 (1995), 274–284.
24. Grigillo, D., Fras, M.K., Petrovic, D., Automated building extraction from IKONOS images in suburban areas. Int. J. Remote Sens. 33:16 (2012), 5149–5170, 10.1080/01431161.2012.659356.
25. Guldogan, O., Rotola-Pukkila, J., Balasundaram, U., Le, T.H., Mannar, K., Chrisna, T.M., Gabbouj, M. 2016. Automated tree detection and density calculation using unmanned aerial vehicles. In: Visual Communications and Image Processing (VCIP), 1-4 IEEE.
26. Heinzel, J.N., Weinacker, H., Koch, B., Prior-knowledge-based single-tree extraction. Int. J. Remote Sens. 32:17 (2011), 4999–5020, 10.1080/01431161.2010.494633.
27. Höfle, B., Vetter, M., Pfeifer, N., Mandlburger, G., Stötter, J., Water surface mapping from airborne laser scanning using signal intensity and elevation data. Earth Surf. Proc. Land. 34:12 (2009), 1635–1649, 10.1002/esp.1853.
28. Hough, P.V.C., 1962. Hough Method and means for recognizing complex patterns (1962). U.S. Patent 3 069 654, 18 December.
29. IPGRI. 1999. Descriptors for Citrus. International Plant Genetic Resources Institute, Rome, Italy. 75p. ISBN-10: 92-9043-425-2.
30. Jaakkola, A., Hyyppa, J., Kukko, A., Yu, X., Kaartinen, H., Lehtomaki, M., Lin, Y., A low-cost multi-sensoral mobile mapping system and its feasibility for tree measurements. ISPRS J. Photogramm Remote Sens. 65:6 (2010), 514–522, 10.1016/j.isprsjprs.2010.08.002.
31. Jiang, H., Chen, S., Li, D., Wang, C., Yang, J., Papaya tree detection with UAV images using a GPU-accelerated scale-space filtering method. Remote Sens, 9(7), 2017, 721, 10.3390/rs9070721.
32. Jing, L., Hu, B., Noland, T., Li, J., An individual tree crown delineation method based on multi-scale segmentation of imagery. ISPRS J. Photogramm. Remote Sens. 70:2012 (2012), 88–98, 10.1016/j.isprsjprs.2012.04.003.
33. Kafa, G., Uzun, A., Turgutoglu, E. Canan, I, Oztop, A, Canihos, E. 2010. Citrus growing, Ministry Of Agriculture And Rural Affairs, Prospective Farmer Education Project Through Television (YAYCEP). In: Kafa, G., Canihos, E. (Eds.). No: 54, 1st Edition, 220p. (in Turkish).
34. Kankare, V., Liang, X., Vastaranta, M., Yu, X., Holopainen, M., Diameter distribution estimation with laser scanning based multisource single tree inventory. ISPRS J. Photogramm. Remote Sens. 108 (2015), 161–171, 10.1016/j.isprsjprs.2015.07.007.
35. Ke, Y., Lindi, J., Quackenbush, L.J., A review of methods for automatic individual tree-crown detection and delineation from passive remote sensing. Int. J. Remote Sens. 32:17 (2011), 4725–4747, 10.1080/01431161.2010.494184.
36. Ke, Y., Quackenbush, L.J., A comparison of three methods for automatic tree crown detection and delineation from high spatial resolution imagery. Int. J. Remote Sens. 32:13 (2011), 3625–3647, 10.1080/01431161003762355.
37. Larsen, M., Eriksson, M., Descombes, X., Perrin, G., Brandtberg, T., Gougeon, F.A., Comparison of six individual tree crown detection algorithms evaluated under varying forest conditions. Int. J. Remote Sens. 32:20 (2011), 5827–5852, 10.1080/01431161.2010.507790.
38. Lee, J., Cai, X., Lellmann, J., Dalponte, M., Malhi, Y., Butt, N., Morecroft, M., Schonlieb, C.B., Coomes, D.A., Individual tree species classification from airborne multisensor imagery using robust PCA. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 9:6 (2016), 2554–2567, 10.1109/JSTARS.2016.2569408.
39. Li, L., Li, D., Zhu, H., Li, Y., A dual growing method for the automatic extraction of individual trees from mobile laser scanning data. ISPRS J. Photogramm. Remote Sens. 120 (2016), 37–52, 10.1016/j.isprsjprs.2016.07.009.
40. Lisein, J., Pierrot-Deseilligny, M., Bonnet, S., Lejeune, P., A photogrammetric workflow for the creation of a forest canopy height model from small unmanned aerial system imagery. Forests 4:4 (2013), 922–944, 10.3390/f4040922.
41. Liu, Y., Li, Z., Hayward, R., Walker, R., Jun, H., 2010. Classification of airborne LIDAR intensity data using statistical analysis and hough transform with application to power line corridors. In: Proc. Digital Image Computing: Techniques and Applications 2009, Melbourne, 1–3 December. pp. 462–467.
42. Liu, T., Im, J., Quackenbush, L.J., A novel transferable individual tree crown delineation model based on fishing net dragging and boundary classification. ISPRS J. Photogramm. Remote Sens. 110 (2015), 34–47, 10.1016/j.isprsjprs.2015.10.002.
43. Matsuki, T., Yokoya, N., Iwasaki, A., Hyperspectral tree species classification of japanese complex mixed forest with the aid of lidar data. IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens. 8:5 (2015), 2177–2187, 10.1109/JSTARS.2015.2417859.
44. McKeown, D. Jr., Cochran, S., Ford, S., McGlone, C., Shufelt, J., Yocum, D., Fusion of HYDICE hyperspectral data with panchromatic imagery for cartographic feature extraction. IEEE Trans. Geosci. Rem. Sens. 37:3 (1999), 1261–1277, 10.1109/36.763286.
45. Naesset, E., Airborne laser scanning as a method in operational forest inventory: Status of accuracy assessments accomplished in Scandinavia. Scand. J. For. Res. 22:5 (2007), 433–442, 10.1080/02827580701672147.
46. Nelson, T., Boots, B., Wulder, M.A., Techniques for accuracy assessment of tree locations extracted from remotely sensed imagery. J. Environ. Manage. 74 (2005), 265–271, 10.1016/j.jenvman.2004.10.002.
47. Nevalainen, O., Honkavaara, E., Tuominen, S., Viljanen, N., Hakala, T., Yu, X., Huuppa, J., Saari, H., Pölönen, I., Imai, N.N., Tommaselli, A.M., Individual tree detection and classification with UAV-based photogrammetric point clouds and hyperspectral imaging. Remote Sens., 9(3), 2017, 185, 10.3390/rs9030185.
48. Ok, A.O., Ozdarici-Ok, A. in press. 2-D delineation of individual citrus trees from UAV-based dense photogrammetric surface models. Int. J. Digital Earth. 1–26. doi: 10.1080/17538947.2017.1337820.
49. Ok, A. O. and Ozdarici-Ok, A. 2017b. Detection of citrus trees from UAV DSMs, ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., IV-1/W1, 27-34. doi: 10.5194/isprs-annals-IV-1-W1-27-2017.
50. Ozdarici-Ok, A., Automatic detection and delineation of citrus trees from VHR satellite imagery. Int. J. Remote Sens. 36 (2015), 4275–4296, 10.1080/01431161.2015.1079663.
51. Pix4D, 2017. Pix4D support official web sites, https://support.pix4d.com/hc/en-us/articles/202558689#label103&gsc.tab=0, (Access date: 16.08.2017).
52. Pouliot, D.A., King, D.J., Approaches for optimal automated individual tree crown detection in regenerating coniferous forests. Canadian J. Remote Sens. 31:3 (2005), 255–267, 10.5589/m05-011.
53. Pu, R., Landry, S., A comparative analysis of high spatial resolution IKONOS and WorldView-2 imagery for mapping urban tree species. Remote Sens. Environ. 124 (2012), 516–533.
54. Puissant, A., Rougier, S., Stumpf, A., Object-oriented mapping of urban trees using Random Forest classifiers. Int. J. Appl. Earth Obs. Geoinf. 26:2014 (2014), 235–245.
55. Puliti, S., Orka, H.O., Gobakken, T., Næsset, E., Inventory of small forest areas using an unmanned aerial system. Remote Sens. 7:8 (2015), 9632–9654, 10.3390/rs70809632.
56. Recio, J.A., Hermosilla, T., Ruiz, L.A., Palomar, J., Automated extraction of tree and plot-based parameters in citrus orchards from aerial images. Comput. Electron. Agric. 90 (2013), 24–34, 10.1016/j.compag.2012.10.005.
57. Rizon, M., Yazid, H., Saad, P., Shakaff, A.Y., Saad, A.R., Sugisaka, M., Yaacob, S., Mamat, M.R., Karthigayan, M., Am. J. Appl. Sci. 2:12 (2005), 1606–1609, 10.3844/ajassp.2005.1606.1609.
58. Rosebrock, A. 2014. Detecting circles in images using OpenCV and Hough circles. In Image Processing Tutorials, http://www.pyimagesearch.com/2014/07/21/detecting-circles-images-using-opencv-hough-circles/ (Access date; 05.02.2018).
59. Salami, E., Barrado, C., Pastor, E., UAV flight experiments applied to the remote sensing of vegetated areas. Remote Sens. 6:11 (2014), 11051–11081, 10.3390/rs61111051.
60. Santoro, F., Tarantino, E., Figorito, B., Gualano, S., D'Onghia, A.M., A tree counting algorithm for precision agriculture tasks. Int. J. Digital Earth 6:1 (2013), 94–102, 10.1080/17538947.2011.642902.
61. Sharfi, H.Z.M., Hamdan, N., Sapiran, M.I., Semi-automatic detection and counting of oil palm trees from high spatial resolution airborne imagery. Int. J. Remote Sens. 32:8 (2011), 2095–2115, 10.1080/01431161003662928.
62. Sieberth, T. 2016. Motion blur in digital images-analys, detection and correction of motion blur in photogrammetry, Loughborough University Doctoral dissertation, © Till Sieberth.
63. Sivagami, K.P., Jayanthi, S.K., Aranganayagi, S., Geetha, A., Edge detection using multispectral thresholding. ICTACT J. Image Video Process. 6:4 (2016), 1262–1272, 10.21917/ijivp.2016.0184.
64. Tang, L., Shao, G., Drone remote sensing for forestry research and practices. J. For. Res. 26:4 (2015), 791–797, 10.1007/s11676-015-0088-y.
65. Taud, H., Parrot, J.F., Detection of circular structures on satellite images. Int. J. Remote Sens. 13:2 (1992), 319–335.
66. Thiel, C., Schmullius, C., Comparison of UAV photograph-based and airborne lidar-based point clouds over forest from a forestry application perspective. Int. J. Remote Sens. 38:8–10 (2017), 2411–2426, 10.1080/01431161.2016.1225181.
67. Torresan, C., Berton, A., Carotenuto, F., Di Gennaro, S.F., Gioli, B., Matese, A., Miglietta, F., Vagnoli, C., Zaldei, A., Wallace, L., Forestry applications of UAVs in Europe: a review. Int. J. Remote Sens. 38:8–10 (2017), 2427–2447.
68. TSI, 2017. Turkish Statistical Institute, https://biruni.tuik.gov.tr/bitkiselapp/bitkisel.zul, (Access date; 12.10.2017).
69. Turker, M., Koc-San, D., Building extraction from high-resolution optical spaceborne images using the integration of support vector machine (SVM) classification, Hough transformation and perceptual grouping. Int. J. Appl. Earth Obs. Geoinf. 34 (2015), 58–69, 10.1016/j.jag.2014.06.016.
70. Vauhkonen, J., Ene, L., Gupta, S., Heinzel, J., Holmgren, J., Pitkänen, J., Solberg, S., Wang, Y., Weinacker, H., Hauglin, K.M., Lien, V., Packalén, P., Gobakken, T., Koch, B., Næsset, E., Tokola, T., Maltamo, M., Comparative testing of single-tree detection algorithms under different types of forest. Forest.: Int. J. Forest. Res. 85:1 (2012), 27–40, 10.1093/forestry/cpr051.
71. Vauhkonen, J., Maltamo, M., McRoberts, R.E., Naesset, E. 2014. Introduction to forestry applications of airborne laser scanning. In: Maltamo, M. Naesset, E. Vauhkonen, J. (Eds.). Forestry Applications of Airborne Laser Scanning. Managing Forest Ecosystems, vol. 27. (pp. 1–16). Springer Netherlands.
72. Wallace, L., Musk, R., Lucieer, A., An assessment of the repeatability of automatic forest inventory metrics derived from UAV-borne laser scanning data. IEEE Trans. Geosci. Remote Sens. 52:11 (2014), 7160–7169.
73. Wallace, L., Lucieer, A., Malenovský Z., Turner, D., Vopěnka, P., Assessment of forest structure using two UAV techniques: a comparison of airborne laser scanning and structure from motion (SfM) point clouds. Forests 7:3 (2016), 1–16.
74. Wang, L., Gong, P., Biging, G.S., Individual tree-crown delineation and treetop detection in high-spatial resolution aerial imagery. Photogramm. Eng. Remote Sens. 70 (2004), 351–357.
75. Wu, B., Yu, B., Wu, Q., Huang, Y., Chen, Z., Wu, J., Individual tree crown delineation using localized contour tree methodand airborne LiDAR data in coniferous forests. Int. J. Appl. Earth Observ. Geoinf. 52 (2016), 82–94, 10.1016/j.jag.2016.06.003.
76. Xu, C., Lu, Z., Xu, G., Feng,Z., Tan, H. and Zhang, H. 2015. 3D reconstruction of tree-crown based on the UAV aerial images. Hindawi Publishing Corporation Mathematical Problems in Engineering. vol. 2015 (Article ID 318619) pp. 1–8. doi: 10.1155/2015/318619.
77. Yang, B., Dai, W., Dong, Z., Liu, Y., Automatic forest mapping at individual tree levels from terrestrial laser scanning point clouds with a hierarchical minimum cut method. Remote Sens., 8, 2016, 372, 10.3390/rs8050372.
78. Yin, D., Wang, L., How to assess the accuracy of the individual tree-based forest inventory derived from remotely sensed data: a review. Int. J. Remote Sens. 37:19 (2016), 4521–4553, 10.1080/01431161.2016.1214302.
79. Yuen, H.K., Princen, J., Illingworth, J., Kittler, J. 1989. A comparative study of Hough transform methods for circle finding. In: Alvey Vision Conference (AVC): 169–174. doi:10.5244/C.3.29.
80. Zarco-Tejada, P.J., Diaz-Varela, R., Angileri, V., Loudjani, P., Tree height quantification using very high resolution imageryacquired from an unmanned aerial vehicle (UAV) and automatic 3Dphoto-reconstruction method. Eur. J. Agron. 55 (2014), 89–99.
81. Zhang, C., Zhou, Y., Qiu, F., Individual tree segmentation from LiDAR point clouds for urban forest inventory. Remote Sens. 7 (2015), 7892–7913, 10.3390/rs70607892.
82. Zhen, Z., Quackenbush, L.J., Stehman, S.V., Zhang, L., Agent-based region growing for individual tree crown delineation from airborne laser scanning (ALS) data. Int. J. Remote Sens. 36:3 (2015), 1965–1993, 10.1080/01431161.2015.1030043.