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A Method to Detect Object of Interest from Satellite Imagery based on MSER(Maximally Stable Extremal Regions)
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 Title & Authors
A Method to Detect Object of Interest from Satellite Imagery based on MSER(Maximally Stable Extremal Regions)
Baek, Inhye;
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This paper describes an approach to detect interesting objects using satellite images. This paper focuses on the interesting objects that have common special patterns but do not have identical shapes and sizes. The previous technologies are still insufficient for automatic finding of the interesting objects based on operation of special pattern analysis. In order to overcome the circumstances, this paper proposes a methodology to obtain the special patterns of interesting objects considering their common features and their related characteristics. This paper applies MSER(Maximally Stable Extremal Regions) for the region detection and corner detector in order to extract the features of the interesting object. This paper conducts a case study and obtains the experimental results of the case study, which is efficient in reducing processing time and efforts comparing to the previous manual searching.
MSER(Maximally Stable Extremal Regions);SIFT(Scale Invariant Feature Transform);Conner Detector;Maximally Stable Region;Local Extremum;
 Cited by
K. O. Kim, S. W. Shin, "Trend of Multi-sensor Spartial Imagery Processing Technology," Electronics and Telecommunication Tend, Vol. 20, No. 3, 2005.

B. Bhanu, "Automatic Target Recognition: State of the Art Survey," IEEE Trans. on Aerospace and Electronic Systems, Vol. 22, No. 4, pp. 364-379, 1986.

S. H. Yu, D. H. Kim, S. L. Lee, C. W. chung, S. H. Kim, "SIFT based Image Similarity Search using an Edge Image Pyramid and Interesting Region Detection," Journal of KIISE, Vol. 35, pp. 345-355, 2008.

D. Lowe, "Object Recognition from Local Scale-Invariant Features," Processing of the Seventh IEEE International Computer Vision, Vol. 2, pp. 1155-1157, 1997.

D. Tell, S. Carlsson, "Wide Baseline Point Matching using Affine Invariant Computed from Intensity Profiles," In Proceedings of the 6th European Conference on Computer Vision, Dublin, Ireland, pp. 814-828, 2000.

T. Tuytelaars, L., Van Gool, "Wide Baseline Strereo Matching based on Local, Affinely Invariant Region," In Proceedings of the 11th British Machine Vision Conference, Bristol, UK, pp. 412-425, 2000.

T., Kadir, A. Zisserman, M. Brady, "An Affine Invariant Salient Region Detector," In Proceedings of the 8th European Conference on Computer Vision, Prague, Czech Republic, pp. 345-457, 2004.

N. Mark, A. Alberto, "Feature Extraction and Image Processing," Academic Press, London, pp. 159-163, 2008.

I. Lim, S. Kim, J. Choi, "Detection Method of Objects with a Special Pattern in Satellite Images using Histogram of Gradients(HOG) Feature and Support Vectior Machine(SVM) Classifier," Korean Journal of Remote Sensing, Vol. 30, No. 4, pp. 537-546, 2014. crossref(new window)