Image thresholding framework based on 2D fractional integration and Legendre moments'

Abstract : In this study, the authors present a new image segmentation algorithm based on two-dimensional digital fractional integration (2D-DFI) that was inspired from the properties of the fractional integration function. Although obtaining a good segmentation result corresponds to finding the optimal 2D-DFI order, the authors propose a new alternative based on Legendre moments. This framework, called two dimensional digital fractional integration and Legendre moments' (2D-DFILM), allows one to include contextual information such as the global object shape and exploits the properties of the 2D fractional integration. The efficiency of 2D-DFILM is shown by the comparison to other six competing methods recently published and it was tested on real-world problem.
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A. Nakib, Y. Schulze, E. Petit. Image thresholding framework based on 2D fractional integration and Legendre moments'. IET Image Processing, Institution of Engineering and Technology, 2012, 6 (6), pp.717-727. ⟨hal-00923845⟩

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