The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Wood defect detection has an important influence on the automation of wood industry. In view of the complexity of wood defect segmentation, this paper proposes the hybrid algorithm of genetic algorithm and particle swarm optimization algorithm. Firstly, the contrast of the image is enhanced by the linear transformation function. Then, applying genetic algorithm and particle swarm-genetic hybrid algorithm...
This paper presents an improved discrete quantum particle swarm optimization (IDQPSO) for 2-D maximum entropic multi-threshold image segmentation algorithm. Firstly, particle swarm binary-encoded method based on 2-D threshold is proposed. Additionally, new particle evolution strategy is proposed to avoid converging on local optimum and accelerate searching progress. Additionally, experiments are conducted...
The image thresholding approach based on the basis of 2-D maximum entropy has better segmentation performance by the use of local space information of pixels, but it is unpractical for heavy computation required by this method. In the paper, an image segmentation technology based on cuckoo search and 2-D maximum entropy is presented, which views the seeking of 2-D maximum entropy of the image as a...
In order to obtain the optimal segmentation threshold and get rid of the local optimal solution of image segmentation, this paper reconstructs crossover and mutation rate which will not be zero at any time. Meanwhile, crossover and mutation genetic operations are used to search the optimal segmentation threshold, where the fitness function is the largest two-dimensional entropy function. Then, grey...
This study offers a heuristic genetic algorithm based method for message hiding in a carrier image. This approach focuses on the "before embedding hiding techniques" by trying to find appropriate places in carrier image to embed the message with the least changes of bits. Due to it, segmentation is done in order to convert the LSBs and message strings to the sets of blocks for participation...
This paper proposes a method to search safe landing site using dual-threshold image segmentation algorithm for Chang'e-3 when the digital elevation map is obtained. Aiming at meeting the need of security, the probe ought to choose a flat ground to land at. Thus an improved dual-threshold image segmentation algorithm is proposed to deal with the shadowed and light split regions of obstacles respectively...
This paper discusses the performance evaluation of the Content Based Image Retrieval (CBIR) system using the optimality in selection of feature vector elements. The performance of the CBIR system may be improved by appropriate analysis of the image. Image analysis is still facing problems related to the detection of the objects. In spite of the noticeable achievements using the part based model, the...
In this paper, a new method for unsupervised image segmentation that can be applied to RGB-D (red, green, blue — depth) cameras is presented. The method consists in using a genetic algorithm to optimize the homogeneity of the segmented regions of a depth image. It searches for the best gray level ranges for which the segmentation of the image is closer to the ground truth. Experimental results and...
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...
Image Segmentation is one of the most challenging problems in Computer Vision. This process consists in dividing an image in different parts which share a common property, for example, identify a concrete object within a photo. Different approaches have been developed over the last years. This work is focused on Unsupervised Data Mining methodologies, specially on Graph Clustering methods, and their...
Multi-threshold image segmentation have achieved good results, but multi-threshold searching can be very time consuming, in order to improve the efficiency of multi-threshold searching, in this paper, the Firefly Algorithm is applied to solve multi-threshold searching. With maximum entropy as the optimization objective function, more information of images can be reserved, then using the Firefly Algorithm's...
Image segmentation is an important component of image processing. The improvements of the segmentation efficiency and quality are the two significant issues for each segmentation algorithm. This paper proposed a segmentation algorithm based on the negative selection mechanism of the artificial immune system. The algorithm can extract the occluded target in an infrared image by using a template constructed...
Hidden Markov Random Field (HMRF) model and Finite Mixture Model (FMM) parameter estimation algorithm provides an interesting framework for image segmentation task, hence a technique that capitalizes on the benefits of both algorithms would achieve better performance. In this regard, we propose a new segmentation algorithm which combines with HMRF model and FMM parameter estimation algorithm. Firstly,...
Image segmentation is an important and classic problem in image processing and computer vision. Thresholding is applied to many fields, because of its less computation and stable performance. The key of thresholding method is to determine the adaptive threshold. In order to segment biological image effectively, a new adaptive thresholding method is proposed. First, two dimension minimum entropy is...
A study of core problem in the packaged granary grain intelligent detection based on image recognition was conducted, and an intelligent detection method combining Fisher criterion with Adaptive Genetic Algorithm was used to solve it. We took the actual scene video as the analysis object, and the constructed Fisher criterion as the fitness function of Genetic Algorithm, while we presented a local...
Image segmentation is a fundamental step for many image analysis and preprocessing tasks. In segmentation, minimum cross entropy (MCE) based multilevel thresholding is regarded as an effective improvement over the bi-level method. However, it is very time consuming for real-time applications. In this paper, a fast threshold selection method based on bacterial foraging optimization (BFO) algorithm...
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...
The development of power system video surveillance technology base on the development of image segmentation technology. Maximum variance between clusters (Otsu) is an complex, time-consuming image segmentation method. In light of this character, an optimization method. i. e. GA and PSO hybrid algorithm, which based the genetic algorithm (GA) and particle swarm optimization (PSO) is utilized to optimize...
Simulated Annealing (SA), Tabu Search (TS), Genetic Algorithm (GA), and Ant Colony System (ACS) are four of the main algorithms for solving challenging problems of intelligent systems. In this paper, these four techniques and three novel hybrid combinations of them are proposed to mammogram segmentation. The novel hybrid algorithms consist of a Sequential TS-ACS, a Hybrid ACS/TS, and a Sequential...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.