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Enhancement of Temperature Feature as a Result of Double Source Image Fusion

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Języki publikacji
EN
Abstrakty
EN
In this paper a double source images fusion algorithm is presented. Its task is to enhance temperature feature of objects located on the scene. Presented solution is design to be executed in real-time environment. It consists of three stages: in the first part the differences between acquired double source images are examined in order to determine their intersection. Then for each analysed image the contours of all objects located on the scene are determined. This operation is essential to solve disparition issue. In the last stage, based on determined contours and their match coefficient the images are fused. The enhanced temperature feature is displayed on one image acquired from day-light camera.
Twórcy
autor
  • Institute of Applied Computer Science on Lodz University of Technology, Poland
autor
  • Institute of Applied Computer Science on Lodz University of Technology, Poland
autor
  • Institute of Applied Computer Science on Lodz University of Technology, Poland
  • Institute of Applied Computer Science on Lodz University of Technology, Poland
  • Institute of Applied Computer Science on Lodz University of Technology, Poland
autor
  • Institute of Applied Computer Science on Lodz University of Technology, Poland
Bibliografia
  • [1] J. Han, S. Yang, B. Lee, A Novel 3-D Color Histogram Equalization Method With Uniform 1-D Gray Scale Histogram, IEEE Transactions on Image Processing, Vol. 20, No. 2, pp. 506-512, 2011
  • [2] S. Jeżewski, D. Sankowski, W. Dadan, Koncepcja autonomicznego robota pola walki przeznaczonego do zadań zwiadu i wykrywania min, Automatyka, Vol. 13, pp. 1107-1116, 2009
  • [3] S. Suzuki, K. Abe, Topological Structural Analysis of Digitized Binary Images by Border Following, Computer Vision, Graphics, and Image Processing, Vol. 30, No. 1, pp. 32-46, 1985
  • [4] J. Canny, A Computational Approach To Edge Detection, Pattern Analysis and Machine Intelligence, IEEE Transactions on, Vol. 6, pp. 679-698, 1986
  • [5] R. Kimmel, A.M. Bruckstein, Regularized Laplacian Zero Crossings as Optimal Edge Integrators, International Journal of Computer Vision, Vol. 53, No. 3, pp. 225-243, 2003
  • [6] L.R. Liang, C.G. Looney, Competitive fuzzy edge detection, Applied soft computing, Vol. 3, No. 2, pp. 123-137, 2003
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Bibliografia
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bwmeta1.element.baztech-02488285-ce01-48d2-8d11-deed6efac02d
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