Fuzziness measure approach to automatic histogram threshold
Abstract
In this paper, an automatic histogram threshold approach based on a fuzziness measure is presented. This work is an improvement of an existing method. Using fuzzy logic concepts, the problems to find a minima of a criterion function are avoided. Similarity between gray levels is the key to find an optimal threshold. Two initial regions of gray levels, located at the boundaries of the histogram, are defined. Then, using an index of fuzziness, a similarity process is started to find the threshold point. A significant contrast between objects and background is assumed. Previous histogram equalization is used in small contrast images. No pior knowledge of the image is required.
Fields of Study & Subjects
Neural Networks and Applications
Publication details
- Journal / source
- Computational Vision and Medical Image Processing
- Publisher
- CRC Press
- Pages
- 295–300
- Publication date
- 22 January 2026
- Language
- EN
- Document type
- Book chapter