探索元胞自动机中用于图像分割的各种邻域

2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP) Pub Date : 2016-09-01 DOI:10.1109/ICCP.2016.7737155

A. Andreica, L. Dioşan, Andreea Sandor

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引用次数: 2

摘要

本文首先介绍了二维元胞自动机中不同邻域的探索结果，并将其应用于复杂的图像自动分割任务中。数值实验已经在几个真实世界和合成图像上进行了，这些图像的地面真相是已知的，因此能够通过将获得的分割图像与正确的分割进行比较来计算算法的性能。为此，使用了DICE系数，这是文献中发现的最流行的相似性度量之一。所得结果为进一步改进基于元胞自动机的图像分割算法提供了有价值的参考。

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Exploring various neighborhoods in Cellular Automata for image segmentation

This paper presents the first results obtained by exploring different neighborhoods in two-dimensional Cellular Automata applied for the difficult task of automatic image segmentation. Numerical experiments have been performed on several real-world and synthetic images for which the ground truth is known, being therefore able to compute the algorithm performance by comparing the obtained segmented image with the correct segmentation. To this purpose, the DICE coefficient has been used, which is one of the most popular similarity measures found in the literature. Obtained results bring valuable input that could help further improve the algorithms based on Cellular Automata applied to image segmentation.

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2016 IEEE 12th International Conference on Intelligent Computer Communication and Processing (ICCP)

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