Speeding up the Köhler's method of contrast thresholding

Guillaume Noyel (1, 2, 3)

1 IPRI - International Prevention Research Institute
2 SIGPH@iPRI - University of Strathclyde Institute of Global Public Health
3 University of Strathclyde [Glasgow]

Köhler's method is a useful multi-thresholding technique based on boundary contrast. However, the direct algorithm has a too high complexity-O(N 2) i.e. quadratic with the pixel numbers N-to process images at a sufficient speed for practical applications. In this paper, a new algorithm to speed up Köhler's method is introduced with a complexity in O(N M), M is the number of grey levels. The proposed algorithm is designed for parallelisation and vector processing , which are available in current processors, using OpenMP (Open Multi-Processing) and SIMD instructions (Single Instruction on Multiple Data). A fast implementation allows a gain factor of 405 in an image of 18 million pixels and a video processing in real time (gain factor of 96).

Mots clés: parallelisation; pattern recognition; vector processing; boundary contrast; segmentation; Köhler multi-thresholding; fast image segmentation

Domaines: Vision par ordinateur et reconnaissance de formes [cs.CV]; Traitement du signal et de l'image [eess.SP]; Calcul parallèle, distribué et partagé [cs.DC]; Traitement des images [eess.IV]; Complexité [cs.CC]

Guillaume Noyel. Speeding up the Köhler's method of contrast thresholding. IEEE International Conference on Image Processing ICIP 2017, IEEE, Sep 2017, Beijing, China. ⟨10.1109/ICIP.2017.8296295⟩. ⟨hal-01561475v2⟩