@inbook{d84ea1b0f15042e4b0c7e317cde2250f,
title = "Fuzzy Entropy Approaches for Image Segmentation",
abstract = "Images extracted from uncontrolled environments possesses different complexities that affects processing tasks. It also demerit the performance of segmentation approaches in specific when are used thresholding mechanism. The alternative is to use methods that are able to manage uncertainties and ambiguities presented in the pixel{\textquoteright}s classification. Fuzzy entropy methods then are interesting alternatives that permits to handle the situations described above. This chapter then introduces the concepts that permits to use evolutionary algorithms to find the best configuration of fuzzy entropy approaches for images segmentation. This chapter is theoretical, but it also encourages the reader to experiment and apply the concepts using any evolutionary approach.",
author = "Diego Oliva and {Abd Elaziz}, Mohamed and Salvador Hinojosa",
year = "2019",
doi = "10.1007/978-3-030-12931-6_11",
language = "English",
series = "Studies in Computational Intelligence",
publisher = "Springer Verlag",
pages = "141--147",
booktitle = "Studies in Computational Intelligence",
address = "Germany",
}