Bi-Level Image Thresholding obtained by means of Kaniadakis Entropy
This work addresses image processing for segmentation tasks, but it is incremental as it adapts an existing entropy framework to a specific application.
The paper tackles the problem of bi-level image thresholding by applying Kaniadakis entropy within a maximum entropy principle, resulting in a method that demonstrates an abrupt transition in image appearance and is compared to Tsallis entropy-based approaches.
In this paper we are proposing the use of Kaniadakis entropy in the bi-level thresholding of images, in the framework of a maximum entropy principle. We discuss the role of its entropic index in determining the threshold and in driving an "image transition", that is, an abrupt transition in the appearance of the corresponding bi-level image. Some examples are proposed to illustrate the method and for comparing it to the approach which is using the Tsallis entropy.