Building Detection Using Enhanced HOG-LBP Features and Region Refinement Processes

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

Volumn 10, Issue 3, 2017, Pages 888-905

  Konstantinidis, Dimitrios ^a   Stathaki, Tania ^a   Argyriou, Vasileios ^b   Grammalidis, Nikolaos ^c  

^a IMPERIAL COLLEGE LONDON   (United Kingdom)

^b KINGSTON UNIVERSITY   (United Kingdom)

^c INFORMATION TECHNOLOGIES INSTITUTE   (Greece)

Author keywords

Buildings; feature extraction; image segmentation; satellite applications; vegetation; water

Indexed keywords

BUILDINGS; IMAGE PROCESSING; IMAGE SEGMENTATION; REMOTE SENSING; SATELLITES; VEGETATION; WATER;

BUILDING RECOGNITION; HIGH RESOLUTION SATELLITE IMAGES; HISTOGRAMS OF ORIENTED GRADIENTS (HOG); LOCAL BINARY PATTERNS; REFINEMENT PROCESS; SATELLITE APPLICATIONS; SUPPORT VECTOR MACHINE CLASSIFIERS; URBAN ENVIRONMENTS;

FEATURE EXTRACTION;

BUILDING; DETECTION METHOD; HISTOGRAM; IMAGE PROCESSING; PATTERN RECOGNITION; SATELLITE IMAGERY; SUPPORT VECTOR MACHINE; VEGETATION INDEX;

EID: 85027435893     PISSN: 19391404     EISSN: 21511535     Source Type: Journal    
DOI: 10.1109/JSTARS.2016.2602439     Document Type: Article

References (46)

1. L. Theng, "Automatic building extraction from satellite imagery," Eng. Lett., vol. 13, no. 3, pp. 1-5, Nov. 2006.
2. K. Karantzalos and D. Argialas, "A region-based level set segmentation for automatic detection of man-made objects from aerial and satellite images," Photogramm. Eng. Remote Sens., vol. 75, no. 6, pp. 667-677, 2009.
3. D. Singh, R. Maurya, A. Shukla, M. Sharma, and P. Gupta, "Building extraction from very high resolution multispectral images using NDVI based segmentation and morphological operators," in Proc. Students Conf. Eng. Syst., Mar. 2012, pp. 1-5.
4. T. Hermosilla, L. Ruiz, J. Recio, and J. Estornell, "Evaluation of automatic building detection approaches combining high resolution images and LiDAR data," Remote Sens., vol. 3, no. 6, pp. 1188-1210, 2011.
5. B. Sirmacek and C. Unsalan, "Urban-area and building detection using SIFT keypoints and graph theory," IEEE Trans. Geosci. Remote Sens., vol. 47, no. 4, pp. 1156-1167, Apr. 2009.
6. B. Sirmacek and C. Unsalan, "A probabilistic framework to detect buildings in aerial and satellite images," IEEE Trans. Geosci. Remote Sens., vol. 49, no. 1, pp. 211-221, Jan. 2011.
7. P. Hough, "Method and means for recognizing complex patterns," U.S. Patent 3 069 654, Dec. 18, 1962.
8. T. Kim and J. Muller, "Development of a graph-based approach for building detection," Image Vision Comput., vol. 17, no. 1, pp. 3-14, 1999.
9. D. Haverkamp, "Automatic building extraction from IKONOS imagery," in Proc. Amer. Soc. Photo Remote Sens., 2004, pp. 23-28.
10. D. Woo, Q. Nguyen, Q. N. Tran, D. Park, and Y. Jung, "Building detection and reconstruction from aerial images," in Proc. Int. Soc. Photogramm. Remote Sens. Congr., Beijing, China, 2008, pp. 713-718.
11. S. Vinson, L. Cohen, and F. Perlant, "Extraction of rectangular buildings in aerial images," in Proc. Scand. Conf. Image Anal., 2001.
12. K. Karantzalos and N. Paragios, "Recognition-driven two-dimensional competing priors toward automatic and accurate building detection," IEEE Trans. Geosci. Remote Sens., vol. 47, no. 1, pp. 133-144, Jan. 2009.
13. O. Benarchid et al., "Building extraction using object-based classification and shadow information in very high resolution multispectral images, a case study: Tetuan, Morocco," Can. J. Image Process. Comput. Vision, vol. 4, no. 1, pp. 1-8, Jan. 2013.
14. S. Kluckner and H. Bischof, "Image-based building classification and 3d modeling with super-pixels," in Proc. Int. Soc. Photogramm. Remote Sens. Photogramm. Comput. Vis. Image Anal., 2010, pp. 291-296.
15. A. Shackelford and C. Davis, "A combined fuzzy pixel-based and objectbased approach for classification of high-resolution multispectral data over urban areas," IEEE Trans. Geosci. Remote Sens., vol. 41, no. 10, pp. 2354-2363, Oct. 2003.
16. Z. Sheng-hua, H. Jian-jun, and X. Wei-xin, "A new method of building detection from a single aerial photograph," in Proc. 9th Int. Conf. Signal Process., Oct. 2008, pp. 1219-1222.
17. C. Senaras, M. Ozay, and F. T. Y. Vural, "Building detection with decision fusion," IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 6, no. 3, pp. 1295-1304, Jun. 2013.
18. D. Chai, W. Förstner, and M. Y. Yang, "Combine Markov random fields and marked point processes to extract building from remotely sensed images," in Proc. ISPRS Ann. Photogramm. Remote Sens. Spatial Inf. Sci., 2012, pp. 1219-1222.
19. Ö. Ö. Karadaǧ, C. Senaras, and F. T. Y. Vural, "Segmentation fusion for building detection using domain-specific information," IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 8, no. 7, pp. 3305-3315, Jul. 2015.
20. J. Femiani, E. Li, A. Razdan, and P. Wonka, "Shadow-based rooftop segmentation in visible band images," IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 8, no. 5, pp. 2063-2077, May 2015.
21. D. Konstantinidis, T. Stathaki, V. Argyriou, and N. Grammalidis, "A probabilistic feature fusion for building detection in satellite images," in Proc. 10th Int. Conf. Comput. Vision Theory Appl., 2015, pp. 205-212.
22. N. Dalal and B. Triggs, "Histograms of oriented gradients for human detection," in Proc. IEEE Conf. Comput. Vision Pattern Recognit., Jun. 2005, vol. 1, pp. 886-893.
23. T. Ojala, M. Pietikainen, and D. Harwood, "Performance evaluation of texture measures with classification based on Kullback discrimination of distributions," in Proc. Int. Conf. Pattern Recognit., Oct. 1994, vol. 1, pp. 582-585.
24. T. Ojala, M. Pietikainen, and D. Harwood, "A comparative study of texture measures with classification based on featured distributions," Pattern Recognit., vol. 29, no. 1, pp. 51-59, Jan. 1996.
25. X. Wang, T. Han, and S. Yan, "An HOG-LBP human detector with partial occlusion handling," in Proc. Int. Conf. Comput. Vision, Sep. 2009, pp. 32-39.
26. J. Zhang, K. Huang, Y. Yu, and T. Tan, "Boosted local structured HOGLBP for object localization," in Proc. Int. Conf. Comput. Vision Pattern Recognit., Jun. 2011, pp. 1393-1400.
27. A. Fitch, A. Kadyrov, W. Christmas, and J. Kittler, "Fast robust correlation," IEEE Trans. Image Process., vol. 14, no. 8, pp. 1063-1073, Aug. 2005.
28. A. Dempster, N. Laird, and D. Rubin, "Maximum likelihood from incomplete data via the EM algorithm," J. Roy. Statist. Soc. B, vol. 39, no. 1, pp. 1-38, 1977.
29. J. Platt, "Probabilistic outputs for support vector machines and comparisons to regularized likelihood methods," in Advances in Large Margin Classifiers. Cambridge, MA, USA: MIT Press, 1999, pp. 61-74.
30. F. Bianconi and A. Fernndez, "On the occurrence probability of local binary patterns: A theoretical study," J. Math. Imag. Vision, vol. 40, no. 3, pp. 259-268, 2011.
31. M. Pietikainen, A. Hadid, G. Zhao, and T. Ahonen, "Local binary patterns for still images," in Computer Vision Using Local Binary Patterns, vol. 40 (Computational Imaging and Vision). London, U.K.: Springer, 2011, pp. 13-47.
32. J. Xiao and G. Wu, "A robust and compact descriptor based on center-symmetric LBP," in Proc. Int. Conf. Image Graph., Aug. 2011, pp. 388-393.
33. S. Junding, Z. Shisong, and W. Xiaosheng, "Image retrieval based on an improved CS-LBP descriptor," in Proc. IEEE Int. Conf. Inf. Manag. Eng., Apr. 2010, pp. 115-117.
34. W. Xiaosheng and S. Junding, "An effective texture spectrum descriptor," in Proc. Int. Conf. Inf. Assur. Security, Aug. 2009, vol. 2, pp. 361-364.
35. P. Huber, Robust Statistics (Wiley Series in Probability and Statistics). New York, NY, USA: Wiley, 1981.
36. N. Dalal, "Finding people in images and videos," Ph.D. dissertation, Nat. Polytechn. Grenoble, Grenoble, France, Jul. 2006.
37. J. Rouse, R. Haas, J. Scheel, and D. Deering, "Monitoring vegetation systems in the great plains with ERTS," in Proc. 3rd Earth Resource Technol. Satell. Symp., 1974, vol. 1, pp. 48-62.
38. N. Otsu, "Athreshold selectionmethod from gray-level histograms," IEEE Trans. Syst. Man Cybern., vol. 9, no. 1, pp. 62-66, Jan. 1979.
39. S. McFeeters, "Using the normalized difference water index (NDWI) within a geographic information system to detect swimming pools for mosquito abatement: A practical approach," Remote Sens., vol. 5, pp. 3544-3561, 2013.
40. R. Tibshirani, G. Walther, and T. Hastie, "Estimating the number of clusters in a data set via the gap statistic," J. Roy. Stat. Soc. B, vol. 63, pp. 411-423, 2001.
41. D. L. Olson and D. Delen, Advanced Data Mining Techniques, 1st ed. New York, NY, USA: Springer, 2008, p. 138.
42. P. Viola and M. Jones, "Rapid object detection using a boosted cascade of simple features," in Proc. IEEE Conf. Comput. Vis. Pattern Recognit., 2001, vol. 1, pp. 511-518.
43. R. Lienhart and J. Maydt, "An extended set of Haar-like features for rapid object detection," in Proc. Int. Conf. Image Process., 2002, vol. 1, pp. 900-903.
44. P. N. Belhumeur, J. P. Hespanha, and D. J. Kriegman, "Eigenfaces vs. fisherfaces: Recognition using class specific linear projection," IEEE Trans. Pattern Anal. Mach. Intell., vol. 19, no. 7, pp. 711-720, Jul. 1997.
45. D. Chaudhuri, N. K. Kushwaha, A. Samal, and R. C. Agarwal, "Automatic building detection from high-resolution satellite images based on morphology and internal gray variance," IEEE J. Sel. Topics Appl. Earth Observ. Remote Sens., vol. 9, no. 5, pp. 1767-1779, May 2016.
46. J. Liu, T. Fang, and D. Li, "Shadow detection in remotely sensed Iimages based on self-adaptive feature selection," IEEE Trans. Geosci. Remote Sens., vol. 49, no. 12, pp. 5092-5103, Dec. 2011.