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

A. Nakib (1) , Y. Schulze (1) , E. Petit (1)

1 LISSI - Laboratoire Images, Signaux et Systèmes Intelligents

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.

Domaines: Analyse numérique [cs.NA]

A. Nakib, Y. Schulze, E. Petit. Image thresholding framework based on 2D fractional integration and Legendre moments'. IET Image Processing, 2012, 6 (6), pp.717-727. ⟨hal-00923845⟩