Adaptive local thresholding with fuzzy-validity-guided spatial partitioning

This paper describes a new method for image segmentation in which both pixel location and intensity similarity are taken into account. The proposed approach can be regarded as adaptive local thresholding since we focus on the analysis of local rather than global features. By applying the validity-guided fuzzy c-means algorithm, the spatial partitioning of an image into sub-regions in our method becomes context-oriented and fully automatic, unlike conventional local techniques. Experimental results indicate that the algorithm possesses robustness to uneven illumination, noise and presence of shadows