The Combination of Local Fuzzy-Entropy-Based Transition Region Extraction with Otsu Thresholding Method for Image Segmentation

Transition region based thresholding is a newly developed approach for image segmentation in recent years, and the Otsu method is a commonly used technique for image thresholding segmentation. Each has its own advantage and disadvantage. In this paper, we present a novel local fuzzy entropy-based transition region extraction method (LFE-TREM) and its combination with Otsu method, which effectively reduces the effects of both Gaussine and pepper & salt noise. Experimental results demonstrate that the combination of LFETREM and Otsu method significantly outperforms the conventional transition region extraction and segmentation results, which is much robust in noisy images.