Journal
INFORMATION FUSION
Volume 68, Issue -, Pages 37-45Publisher
ELSEVIER
DOI: 10.1016/j.inffus.2020.10.020
Keywords
Image thresholding; Image processing; Adaptive binarization; Fuzzy integrals; Aggregation functions
Funding
- Programma Operativo Nazionale FSEFESR Ricerca Innovazione 2014-2020, Italy
- Asse I Capitale Umano, Italy
- Azione I.1 Dottorati Innovativi con caratterizzazione industriale, Italy
- MIUR (Italy) [DOT1728107]
- VEGA, Slovakia [1/0614/18, 1/0545/20, TPID2019-108392GB-I00 (AEI/10.13039/501100011033)]
- Spain of the Government of Navarra [PC093-094 TFIPDL]
Ask authors/readers for more resources
This paper introduces a new adaptive binarization technique FLAT based on fuzzy integral images, as well as new generalizations of different fuzzy integrals and a modified design of SAT. Experimental results demonstrate that the proposed methodology produces better thresholds than other global and local thresholding algorithms.
Classic adaptive binarization methodologies threshold pixels intensity with respect to adjacent pixels exploiting integral images. In turn, integral images are generally computed optimally by using the summed-area-table algorithm (SAT). This document presents a new adaptive binarization technique based on fuzzy integral images. Which, in turn, this technique is supported by an efficient design of a modified SAT for generalized Sugeno fuzzy integrals. We define this methodology as FLAT (Fuzzy Local Adaptive Thresholding). Experimental results show that the proposed methodology produced a better image quality thresholding than well-known global and local thresholding algorithms. We proposed new generalizations of different fuzzy integrals to improve existing results and reaching an accuracy approximate to 0.94 on a wide dataset. Moreover, due to high performances, these new generalized Sugeno fuzzy integrals created ad hoc for adaptive binarization, can be used as tools for grayscale processing and more complex real-time thresholding applications.
Authors
I am an author on this paper
Click your name to claim this paper and add it to your profile.
Reviews
Recommended
No Data Available