Subject: Computer Science And Mathematics, Applied Mathematics Keywords: image segmentation; gray level thresholds; neutrosophic information; neutrosophic certainty
Online: 31 August 2020 (07:53:55 CEST)
This article presents a new method of segmenting images with gray levels. The method is based on determining several thresholds for separation of gray levels. The determination of these thresholds is done using the certainty of the neutrosophic information. The concept of this method can be stated simply: to choose the local maximums for the neutrosophic certainty.
ARTICLE | doi:10.20944/preprints202005.0167.v1
Subject: Computer Science And Mathematics, Applied Mathematics Keywords: neutrosophic information; Onicescu information energy; image segmentation; gray level image threshold
Online: 10 May 2020 (14:41:04 CEST)
This article presents a method of segmenting images with gray levels that uses Onicescu's information energy calculated in the context of the neutrosophic theory. Starting from the information energy calculation for complete neutrosophic information, it is shown how to extend its calculation for incomplete and inconsistent neutrosophic information. The segmentation method is based on calculation of thresholds for separating the gray levels using the local maximum points of the Onicescu information energy.
ARTICLE | doi:10.20944/preprints201906.0248.v1
Subject: Computer Science And Mathematics, Computer Vision And Graphics Keywords: image segmentation; neutrosophic information; Shannon entropy; gray level image threshold
Online: 25 June 2019 (08:48:22 CEST)
This article presents a new method of segmenting grayscale images by minimizing Shannon's neutrosophic entropy. For the proposed segmentation method, the neutrosophic information components, i.e., the degree of truth, the degree of neutrality and the degree of falsity are defined taking into account the belonging to the segmented regions and at the same time to the separation threshold area. The principle of the method is simple and easy to understand and can lead to multiple thresholds. The efficacy of the method is illustrated using some test gray level images. The experimental results show that the proposed method has good performance for segmentation with optimal gray level thresholds.