Comparison of selected methods of characteristic point detection in satellite images

• Autorzy: Kulawik J.

Identyfikatory

DOI

10.15199/48.2018.01.35

Warianty tytułu

PL

Porównanie wybranych metod wykrywania charakterystycznych punktów w obrazach satelitarnych

• Języki publikacji: EN

Abstrakty

EN

The article presents two methods of detecting objects in images of the surface of the earth from the air. The search was performed using local characteristic features, i.e. key points. In the first method, the corner detection was supplied using the Harris & Stephens algorithm. The descriptors were built for detection key points by the FREAK algorithm. In the second method the blobs were provided by the SURF algorithm. The descriptors were built by the SURF algorithm. After the usage of the above methods, a comparison was made. The obtained results were shown on the example images.

PL

W artykule przedstawiono dwa przykłady detekcji obiektów w zdjęciach powierzchni ziemi z powietrza. Wyszukiwanie wykonano przy użyciu cech charakterystycznych. W pierwszym przykładzie dokonano detekcji narożników przy użyciu algorytmu Harris & Stephens. Następnie zbudowano deskryptory do znalezionych punktów kluczowych w oparciu o algorytm FREAK. W drugim przykładzie zastosowano metodę SURF do odnalezienia plamek i zbudowania ich deskryptorów. Po użyciu powyższych metod dokonano porównania. Uzyskane wyniki zaprezentowano na przykładowych zdjęciach.

Słowa kluczowe

EN

corner detection; object detection; feature detection; descriptor

PL

wykrywanie narożników; wykrywanie obiektu; wykrywanie cech; deskryptor

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2018
• Tom: R. 94, nr 1
• Strony: 139--143
• Opis fizyczny: Bibliogr. 26 poz., fot., tab.

Twórcy

autor

Kulawik J.

• Czestochowa University of Technology, Institute of Computer and Information Sciences, ul. Dąbrowskiego 73, 42-201 Czestochowa, Poland

Bibliografia

• [1] R. Tadeusiewicz, P. Korohoda, Komputerowa analiza i przetwarzanie obrazów. Wydawnictwo Fundacji Postępu Telekomunikacji Kraków, (1997)
• [2] S. Gauglitz, T. H¨ollerer, and M. Turk. Evaluation of interest point detectors and feature descriptors for visual tracking. International Journal of Computer Vision, (2011), pages 1–26
• [3] C. Harris and M. Stephens, A combined corner and edge detector. Proceedings of the 4th Alvey Vision Conference, (1988), pp. 147–151
• [4] D. Lowe. Object recognition from local scale-invariant features. In Computer Vision. The Proceedings of the Seventh IEEE International Conference on, vol. 2 (1999) Ieee, pp. 1150–1157
• [5] E. Rosten and T. Drummond. Machine learning for high speed corner detection. Computer Vision–ECCV 2006, pp. 430–443
• [6] Bay H., Tuytelaars T., Van Gool L., SURF: Speeded-up robust features, [w:] Lecture Notes in Computer Science, t. 3951 (2006), pp. 404-417
• [7] A. Alahi, R. Ortiz, and P. Vandergheynst. Freak: Fast retina key point. In CVPR, 2012. 2
• [8] Chaitanya Malladi, Detection of Objects in Satellite images using Supervised and Unsupervised Learning Methods, URL: http://www.divaportal.se/smash/get/diva2:1119048/FULLTEXT01. pdf, (2017)
• [9] Gong Cheng, Junwei Han, A Survey on Object Detection in Optical Remote Sensing Images, DOI: 10.1016/j.isprsjprs.2016.03.014, arXiv:1603.06201, (2016)
• [10] Gong Cheng, Junwei Han, Xiaoqiang Lu, Remote Sensing Image Scene Classification: Benchmark and State of the Art, DOI: 10.1109/JPROC.2017.2675998, arXiv:1703.00121, (2017)
• [11] Qizhi Xu, Yun Zhang & Bo Li, Improved SIFT match for optical satellite images registration by size classification of blob-like structures, Remote Sensing Letters Vol. 5 , Iss. 5, (2014)
• [12] Mohamed Tahoun, El Rahman Shabayek, Ralf Reulke, Aboul Ella Hassanien, Co-registration of Satellite Images Based on Invariant Local Features, Advances in Intelligent Systems and Computing book series (AISC, volume 323), Intelligent Systems'2014, pp 653-660
• [13] J. Bobulski, H. Piech, Road signs recognition with twodimensional hidden Markov models, Przegląd Elektrotechniczny, 91, 2/2015, 123-126
• [14] V. V. Hnatushenko, O. O. Kavats, M. Kubanek, Y. O. Kibukevych, Conditions and limitations of digital satellite image pre-processing for the further 3D modeling. Journal of Applied Mathematics and Computational Mechanics, Volume 15 (2016), Issue 3, pp 57-65
• [15] Choraś Michał, Image Processing Methods in Person Identification Applications - Ear Biometrics, Electrotechnical Review (Przegląd Elektrotechniczny) no. 4/81 (2005), 38-41
• [16] Choraś Michał, Ear biometrics: feature extraction methods based on geometrical parameters, Przegląd Elektrotechniczny (Electrotechnical Review) no. 12/2006, pp. 5-10, (written in Polish)
• [17] M. Kubanek, D. Smorawa, Verification of Identity Based on Palm Vein and Palm-Print. Advances in Intelligent Systems and Computing, Soft Computing in Computer and Information Science, Volume 342 (2015), pp 139-146, Springer
• [18] D. Smorawa, M. Kubanek, Biometric Systems Based of Palm Vein Patterns. Journal of Telecommunications and Information Technology, Volume 2 (2015), pp 18-22
• [19] Forczmański Paweł, Kukharev Georgy, Shchegoleva Nadezdha, 2012, An algorithm of face recognition under difficult lighting conditions, Przegląd Elektrotechniczny (Electrical Review), r. 88 No. 10b/2012, pp. 201-204.
• [20] M. Borowska, A. Kitlas, E. Oczeretko, A. Radwański, I. Szarmach, J. Szarmach, Fractal Analysis of Dental Radiographic Images in the Irregular Regions of Interest, Information Technologies in Biomedicine, vol. 2, 2nd International Conference, Kamień Śląski, 2010, June 7-9, (E. Piętka, J. Kawa Ed(s).), Adv. Intelligent Soft Comput. vol. 69, (publ. by) Springer, (2010), pp. 191-199
• [21] Forczmański P., Dziurzański P., System-level hardware implementation of simplified Low-Level color image descriptor, Proceedings 8th International Conference On Computer Recognition Systems CORES 2013, Advances in Intelligent Systems and Computing, vol. 226 (2013), pp. 461-468
• [22] Paweł Forczmański, Andrzej Markiewicz, Two-stage approach to extracting visual objects from paper documents, Machine Vision and Applications, Volume 27 (2016), Issue 8, pp 1243– 1257
• [23] Chen-Chien Hsu, Cheng-Kai Yang, Yi-Hsing Chien, Yin-Tien Wang, Wei-Yen Wang, Chiang-Heng Chien, (2017) Computationally efficient algorithm for vision-based simultaneous localization and mapping of mobile robots, Engineering Computations, Vol. 34 Issue: 4
• [24] Louis-Kenzo Cahier, Tetsuya Ogata, Hiroshi G. Okuno, Incremental probabilistic geometry estimation for robot scene understanding, Robotics and Automation (ICRA) 2012 IEEE International Conference on, pp. 3625-3630, (2012), ISSN 1050-4729
• [25] Bay H., Ess A., Tuytelaars T., Van Gool L., SURF: Speeded- Up Robust Features, [w:] Computer Vision and Image Understanding (CVIU), t. 110 (2008), pp. 346-359
• [26] Zeng C., Wang J., Automated Building Information Extraction and Evaluation from Highresolution Remotely Sensed Data, The University of Western Ontario, Electronic Thesis and Dissertation Repository, (2014)

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).