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A simple and efficient method for segmentation and classification of aerial images

Ahmadi, P ; Sharif University of Technology | 2013

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  1. Type of Document: Article
  2. DOI: 10.1109/CISP.2013.6744061
  3. Publisher: 2013
  4. Abstract:
  5. Segmentation of aerial images has been a challenging task in recent years. This paper introduces a simple and efficient method for segmentation and classification of aerial images based on a pixel-level classification. To this end, we use the Gabor texture features in HSV color space as our best experienced features for aerial images segmentation and classification. We test different classifiers including KNN, SVM and a classifier based on sparse representation. Comparison of our proposed method with a sample of segmentation pre-process based classification methods shows that our pixel-wise approach results in higher accuracy results with lower computation time
  6. Keywords:
  7. Aerial images ; Classification ; Segmentation ; Classification methods ; Computation time ; Gabor texture features ; HSV color spaces ; Sparse representation ; Classification (of information) ; Pixels ; Signal processing ; Image segmentation
  8. Source: Proceedings of the 2013 6th International Congress on Image and Signal Processing, CISP 2013 ; Volume 1 , 2013 , Pages 566-570 ; 9781479927647 (ISBN)
  9. URL: http://ieeexplore.ieee.org/xpl/login.jsp?tp=&arnumber=6744061&url=http%3A%2F%2Fieeexplore.ieee.org%2Fxpls%2Fabs_all.jsp%3Farnumber%3D6744061