Classification and detection of various geographical features from satellite imagery

Abstract

It is a challenging task to classify and detect various geographical features from the satellite imagery of the Earth as well as the celestial bodies. This paper puts forward several pixel based classification algorithms to classify geographical features from the satellite images of the Earth. The recorded experimental results, from a total of 606 satellite images to classify miscellaneous geographical features, demonstrate that the maximum algorithmic performances can approximate to 87%. This paper also addresses a simple algorithm based on edge approximation and circular Hough transformation to detect craters from the satellite imagery of celestial bodies. An online available dataset to detect craters evaluates the performance of the algorithm. In general, all the proposed algorithms are straightforward but in many ways effective.

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“…The detection of both normal (e.g., [1][2][3][4][5][6][7][8][9][10][11][12]) and abnormal (e.g., [13][14][15][16][17][18][19][20][21][22][23][24][25][26][27]) video events is a cardinal chore of a surveillance camerasystem. An automated camera system can provide goodtrajectories of objects.…”