Tag: invatare automata

Abstract 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…

Abstract 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…

Abstract 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…

Abstract 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…

Abstract 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…

Abstract 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…

Abstract 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…

Abstract This paper investigates a novel update rule for multi-state Cellular Automata (CA) in the context of greyscale image segmentation. The update rule is parameterized and takes into account the features of neighbouring cells compared to the features of the current cell. We use the resulting CA to segment several real-world images. During this…

Abstract Traffic scene object detection and recognition is extensively researched in the field of roadside assistance. Due to its importance, many methods have been proposed to solve the classification of objects in traffic and aim classification in different lighting conditions, scaling, orientation and shape of objects. Although most methods for classification are binary classification,…

Abstract 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…