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In this paper, we firstly introduce the path analysis of tracking robot, and then introduce the advantages of immune genetic algorithm (IGA). Thirdly, we combine immune genetic algorithm and OTSU threshold method to segment path of tracking robot. Because of the nonlinear solving process of immune genetic algorithm, for each chromosome, the solution of fitness function is separated. And the genetic...
In this article, a variant quantum inspired genetic algorithm for the determination of the optimal threshold of gray-level images is presented. The proposed algorithm initiates with a population of randomly superposed trial solutions in the form of quantum bits. Subsequently, some deterministic nonlinear point transformations are applied on these solutions to generate randomly interfered solutions...
With advances in intelligent technologies, e.g. ambient intelligence, context-aware, and pervasive systems, much research is now devoted to a computational paradigm that senses and perceives changes in human emotion. This paper presents a context-aware architecture for adaptive emotional sensibility analysis called CAF-ESA (a Context-Aware Framework based Emotional Sensibility Analysis) with adaptive...
Automatic parameter selection for image segmentation is accelerated by means of a genetic algorithm (GA). Issues remain in selecting the population size, number of generations, and termination of the search. As evaluation time and subsequent image batch-processing time, when the algorithm is applied in practice, are important considerations, this paper introduces a time factor into the GA cost function...
A photomosaic is an image assembled from smaller images called tiles. When a photomosaic is viewed from a distance, it resembles a desired target image. The process of photomosaic generation can be viewed as an optimization problem, where a set of tiles needs to be arranged to resemble a target image. We impose a constraint on the number of times a tile image can be repeated in a photomosaic. A randomized...
Image segmentation plays an important and basic role in image processing and pattern recognition. Its purpose is to separate areas that do not superpose each other and to obtain the interested target. During the past few years many algorithms for image segmentation have been proposed. The popular technique is the threshold segmentation because of its simplicity and efficiency. Genetic algorithm is...
A new algorithm for adaptive threshold segmentation based on combining Fisher criterion with location optimization is proposed in this paper. Fisher criterion is taking as the fitness function of Genetic Algorithm (GA), and an adaptive method which is used to calculate crossover probability and mutation probability is presented. Meanwhile, we add a new local optimization operator that solves the disadvantages...
Process of burning coal powder in the boiler is a very complex suspension combustion and very unstable. The technology of image processing is an important way to monitor the status of boilers. In this paper, we use image segmentation operation in this area, and the segmentation process is based on an improved hybrid genetic algorithm. In this algorithm, the simulated annealing algorithms and immune...
Quantitative testing of segmentation algorithms implies rigorous testing against ground truth segmentations. Though under-reported in the literature, the performance of a segmentation algorithm depends on the choice of input parameters. The paper reports wide variety both in evaluation time and segmentation results for an example mean-shift algorithm. When testing extends over an algorithmpsilas parameter...
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