Image thresholding by maximizing the index of nonfuzziness of the 2-D grayscale histogram
Computer Vision and Image Understanding
Multi-scale binarization of images
Pattern Recognition Letters
Statistical Mechanical Analysis of Fuzzy Clustering Based on Fuzzy Entropy
IEICE - Transactions on Information and Systems
Fuzzy filter based on interval-valued fuzzy sets for image filtering
Fuzzy Sets and Systems
Parametric indices of fuzziness for automated image enhancement
Fuzzy Sets and Systems
Image thresholding using type II fuzzy sets
Pattern Recognition
Pattern Recognition Letters
A hybrid system for detection of masses in digitized mammograms
ISCGAV'10 Proceedings of the 10th WSEAS international conference on Signal processing, computational geometry and artificial vision
A-IFSs entropy based image multi-thresholding
IEA/AIE'10 Proceedings of the 23rd international conference on Industrial engineering and other applications of applied intelligent systems - Volume Part III
Image segmentation using Atanassov's intuitionistic fuzzy sets
Expert Systems with Applications: An International Journal
A new binarization method for non-uniform illuminated document images
Pattern Recognition
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An image can be regarded as a fuzzy subset of a plane. A fuzzy entropy measuring the blur in an image is a functional which increases when the sharpness of its argument image decreases. We generalize and extend the relation “sharper than” between fuzzy sets in view of implementing the properties of a relation “sharper than” between images. We show that there are infinitely many implementations of this relation into an ordering between fuzzy sets (equivalently, images). Relying upon these orderings, we construct classes of fuzzy entropies which are useful for image thresholding by cost minimization. Assuming the image to be a degraded version of an ideal two level image (object/background), a fuzzy entropy can be introduced in a cost functional to force the fitting function to be as close as possible to a two-valued function. The minimization problem is numerically solved, and the results obtained on a synthetic image are reported