Artificial intelligence

Scientific journal

ISSN 2710-1673

ONLINE: ISSN 2710-1681

Select your language


Conditions and limitations of satellite image intellectual processing methods for the further 3D modeling

Hnatushenko V.1, Kavats O.2, Kibukevych Y.2
1 National Metallurgical Academy of Ukraine
2 National Metallurgical Academy of Ukraine

Full text (PDF)

UDC: 528.8.04
Publication Language: Ukrainian
Stuc. intelekt. 2015; 20(1-2):54-62

Abstract: Reviewed and analyzed existing methods, ways and means of recognition of satellite images, defined by their features and drawbacks in terms of three-dimensional modeling of further development areas. Based on the results of the analysis revealed the need for new methods and algorithms for complex extraction of architectural objects. A mathematical description of the main characteristic features of the buildings and their elements (roof).

Keywords: space images, classification, segmentation, recognition, building forms and types of roofs, 3D-models.

References:

  1. Suschevskyy D. Geometric patterns of identification and visualization of artificial objects changes the earth'ssurface riznochasovymy images: Thesis. 05.01.01 "Applied geometry, engineering graphics" / D.Suschevskyy.- Dnepropetrovsk: DNU O. Honchar, 2011.
  2. Partovi, T., Bahmanyar R., Krauß, T., Reinartz, P. (2014). Building roof component extraction frompanchromatic satellite images using a clustering-based method. The International Archives of thePhotogrammetry, RemoteSensing andSpatial InformationSciences, Volume XL-3.
  3. Hnatushenko V. Information technology increase spatial fragmentation of digital satellite images based onwavelet transformation and ICA / V. Hnatushenko, O. Kavatsiv // Proceedings of the National University "LvivPolytechnic", a series of "ComputerScience and Information Technology." ‒ 2013. ‒ № 771., 28-32 p.
  4. Classification of the roof. ‒ [Electronic resource]. ‒ Access: http://www.mukhin.ru/stroysovet/kr1/1_01.html.
  5. Chuiqing Zeng, Jinfei Wang. (2014) Automated Building Information Extraction and Evaluation from HighresolutionRemotely Sensed Data // The University of Western Ontario, Electronic Thesis and DissertationRepository.
  6. Lillesand, T.M., Kiefer, R.W., Chipman, J.W. (2008). Remote sensing and image interpretation // Hoboken, NJ:John Wiley & Sons. p.
  7. Irvin, R.B., & McKeown, D.M., (1989). Methods for exploiting the relationship between buildings and theirshadowsin aerial imagery // IEEE Transactions onSystems, Man and Cybernetics, 19(6), 564-575.
  8. Shao, Y., Taff, G.N., Walsh, S.J. (2011). Shadow detection and building-height estimation using IKONOS data// InternationalJournal of RemoteSensing, 32(22), 929-944.

View full text (PDF)