Tag: machine learning

In this paper, we introduce Competitive Unsupervised GrowCut, a cellular automata-based, unsupervised and autonomous algorithm that combines the label merging component of Unsupervised GrowCut with the soft label propagation mechanism of GrowCut. We evaluated our algorithm on two benchmark image segmentation datasets, along with two related methods proposed in the literature. We also provide…

The Shift minimization personnel task scheduling problem (SMPTSP) is a known NP-hard problem. The present paper introduces a novel four-phase meta-heuristic approach for solving the Shift minimization personnel task scheduling problem which consists of an optimal assignment of jobs to multi-skilled employees, such that a minimal number of employees is used and no job…

Extending and optimizing cellular automata to handle 3D volume segmentation is a non-trivial task. First, it does not suffice to simply alter the cell neighborhood (be it von Neumann or Moore), and second, going from 2D to 3D means that the number of operations increases by an order of magnitude, thus GPU acceleration becomes…

This paper presents an edge detection method based on Cellular Automata where the rules are evolved to optimize the edge detection in binary images. This method divides the edge detection problem into two sub-problems: on the one hand it trains the rules to detect the edge pixels, on the other hand it trains the…

The main incentive of this paper is to provide an enhanced approach for 2D medical image segmentation based on the Unsupervised Grow Cut algorithm, a method that requires no prior training. This paper assumes that the reader is, to some extent, familiar with cellular automata and their function as they make up the core…

This paper presents the results obtained by investigating a new hybrid topology for the GrowCut algorithm. The main purpose is to study whether choosing neighbors situated at a certain distance from a pixel (in addition to the pixels from a classical neighbourhood) can influence the results of image segmentation. Experiments were performed on real…

The majority of Cellular Automata (CA) described in the literature are binary or three-state. While several abstractions are possible to generalise to more than three states, only a negligible number of multi-state CA rules exist with concrete practical applications. This paper proposes a generic rule for multi-state CA. The rule allows for any number…

Cellular Automata have been considered for a series of applications among which several image processing tasks. The goal of this paper is to investigate such existing methods, supporting the broader goal of identifying Cellular Automata rules able to automatically segment images. With the same broader goal in mind as future work, a detailed description…