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An Adaptive image Enhancement Technique Based on Firefly Algorithm 8

An Adaptive Image Enhancement Technique Based on Firefly Alg...

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8th International symposium on computational intelligence and Design (ISCID)

作者： Ye, Zhiwei Zhao, Wei Ma, Lie Hubei Univ Technol Sch Comp Sci Wuhan Peoples R China

ISBN: (纸本)9781467395878

image enhancement is an important step in image processing, and the enhancement approach based on normalization of incomplete beta function is able to achieve ideal enhanced results. However, it often requires human intervention or is time-consuming to obtain good parameters, which still remains an issue not fully solved. In practice, it is an optimization problem to select the optimal parameters for the method. In the paper, the Firefly Algorithm( FA) is employed to search for the optimal parameters and the acquired optimal parameters are used to generate the gray level transformation curve to improve images. The performance of the proposed method is contrasted with other evolutionary computing methods like genetic algorithm and particle swarm optimization algorithm. Experimental results display that FA is able to gain the optimal parameters effectively and adaptively, which outperforms the other optimization algorithms involved in the paper.

关键词： Firefly Algorithm image enhancement optimal parameters selection

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Fast Adaptive Anisotropic Filtering for Medical image Enhancement

Fast Adaptive Anisotropic Filtering for Medical Image Enhanc...

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ieee International symposium on signal processing and Information Technology

作者： George, Jose Indu, S. P. Network Syst & Technol P Ltd Med Imaging Res Grp Trivandrum Kerala India

ISBN: (纸本)9781424435548

In this paper, Local Structure Tensor (LST) based Adaptive Anisotropic Filtering (AAF) methodology is used for medical image enhancement over different modalities. This filtering framework enhances and preserves anisotropic image structures while suppressing high frequency noise. The goal of this work is to reduce the overall computational cost with minimum risk on accuracy by introducing optimized filternets for local structure analysis and reconstruction filtering. This filtering technique facilitates user interaction and direct control over high frequency contents of the signal. The efficacy of the filtering framework is evaluated by testing the system with medical images of different modalities. The results are compared using three different quality measures. Experimental results show that a good level of noise reduction along with structure enhancement can be achieved in the adaptively filtered images.

关键词： Adaptive Anisotropic Filtering Local Structure Tensor Filternet Filter Optimization

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Video saurus system: Movement evaluation by a genetic algorithm

Video saurus system: Movement evaluation by a genetic algori...

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ieee International symposium on computational intelligence for Measurement Systems and Applications

作者： Mastronardi, G Bevilacqua, V Politecn Bari DEE I-70125 Bari Italy

ISBN: (纸本)0780377834

In this paper we have addressed the problem of adopting in a combined way a genetic algorithm 131 and the Hough Transform [1,2] for implementing an auto tracking method in a video conference system By applying this method we have been able to track an object that moves slowly following quite parallel trajectories. The proposed algorithm considers just the shape of the object to be tracked and a priori known as a template, without taking into account other several characteristics of images like colour or texture. Because the implementation of Hough transform is a problem of maximising a function with particular constraints, and each run of evaluating Hough transform is time consuming, in this paper we have adopted a particular genetic algorithm to evaluate the rectangular region in which evaluate the Hough Transform [6]. The genetic algorithm used elitistic strategy, fitness sharing 151, mating restriction 141, adaptive rate of mutation and adaptive rate of cross-over with a double crosspoint[3]. Moreover, in this paper, since the evaluation of Hough Transform is very time consuming, we have addressed the strategy of dividing the whole scene in different shorter window in order to partition the evaluating load on parallel DSP.

关键词： Body sensor networks Digital signal processing Filters Genetic algorithms Genetic mutations image edge detection image segmentation Layout Shape Videoconference

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A multi-channel representation for images on quantum computers using the RGBα color space

A multi-channel representation for images on quantum compute...

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7th ieee International symposium on Intelligent signal processing, WISP 2011

作者： Sun, Bo Le, Phuc Q. Iliyasu, Abdullah M. Yan, Fei Garcia, J. Adrian Dong, Fangyan Hirota, Kaoru Department of Computational Intelligence and Systems Science Tokyo Institute of Technology Tokyo Japan

ISBN: (纸本)9781457714016

A Multi-Channel Representation for Quantum image (MCRQI) is proposed to facilitate the further image processing tasks based on the Flexible Representation for Quantum image (FRQI). Channel Swapping Operation, One Channel Operation, are proposed as basic image processing operations on MCRQI representation. The simulation experiment results on classical computer show that the channel information of R G B (color) and α (transparency) can be carried easily on quantum computer by employing three qubits to represent the color space, and also indicate that this MCRQI is very flexible to realize some classic-like operations. The MCRQI provides a foundation not only express image in RGBα color space, but also to explore theoretical and practical aspects of image processing on quantum computer. © 2011 ieee.

关键词： Quantum computers

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Classifiers With a Reject Option for Early Time-Series Classification

Classifiers With a Reject Option for Early Time-Series Class...

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ieee symposium on computational intelligence and Ensemble Learning (CIEL)

作者： Hatami, Nima Chira, Camelia Univ Calif San Diego Dept Ophtalmol 9415 Campus Point Dr La Jolla CA 92093 USA Babes Bolyai Univ Dept Comp Sci Kogalniceanu 400084 Romania

ISBN: (纸本)9781467358538

Early classification of time-series data in a dynamic environment is a challenging problem of great importance in signal processing. This paper proposes a classifier architecture with a reject option capable of online decision making without the need to wait for the entire time series signal to be present. The main idea is to classify an odor/gas signal with an acceptable accuracy as early as possible. Instead of using posterior probability of a classifier, the proposed method uses the "agreement" of an ensemble to decide whether to accept or reject the candidate label. The introduced algorithm is applied to the bio-chemistry problem of odor classification to build a novel Electronic-Nose called Forefront-Nose. Experimental results on wind tunnel test-bed facility confirms the robustness of the forefront-nose compared to the standard classifiers from both earliness and recognition perspectives.

关键词： biochemistry decision making electronic noses probability signal processing test facilities time series wind tunnels

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Wireless Thermometer Based on Bluetooth 4.0 Low-energy 7

Wireless Thermometer Based on Bluetooth 4.0 Low-energy

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7th International symposium on computational intelligence and Design (ISCID)

作者： Li, Hongjie Luo, Jian Univ Elect Sci & Technol China Elect Sci & Technol Res Inst Chengdu Peoples R China

ISBN: (纸本)9781479970056

Based on the analysis of the infrared thermometry principle, using low power Bluetooth4.0 technology and combining software and hardware, a thermometer was designed, which can send temperature data to the mobile phone by Bluetooth4.0. After amplified the infrared temperature sensor signal of the thermometer by a instrumentation amplifier, CC2540 carries on the AD sampling, based on the infrared thermometry principle, to calculate the temperature value. Finally the temperature value will be sent to the mobile phone through the Bluetooth 4.0, and the temperature value can be plotted as a line so that we can clearly observe patient's temperature changes for a long time. Through the actual test, the feasibility of the system was verified.

关键词： thermometer bluetooth4.0 BLE CC2540 infrared temperature sensor sensor signal processing

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Emergent complex behaviors for swarm robotic systems by local rules

Emergent complex behaviors for swarm robotic systems by loca...

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symposium Series on computational intelligence, ieee SSCI 2011 - 2011 ieee Workshop on Robotic intelligence in Informationally Structured Space, RIISS 2011

作者： Chatty, Abdelhak Kallel, Ilhem Gaussier, Philippe Alimi, Adel M. Sfax Tunisia ETIS: Neuro-cybernetic Team Image and Signal Processing Cergy-Pontoise University Paris France

ISBN: (纸本)9781424498840

This paper describes a clustering process taking inspiration from the cemetery organization of ants. The goal of this paper is (i) to show the importance of the local interactions which allow to produces complex and emergent behavior. (ii) To propose a multi-robot systems in the field of clustering objects allowing optimization of: time of convergence, rate of occupation of the objects in the environment and final number of the clusters. And finally (iii) to propose another system with the use of cognitive robots instead of reactive robots in the same field of clustering objects with generic rules which can be used independently of the environment. Series of simulations enable us to discuss and validate the proposed approach. © 2011 ieee.

关键词： Multipurpose robots

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JSEG-based image Segmentation in Computer Vision for Agricultural Mobile Robot Navigation

JSEG-based Image Segmentation in Computer Vision for Agricul...

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ieee International symposium on computational intelligence in Robotics and Automation

作者： Lulio, Luciano C. Tronco, Mario L. Porto, Arthur J. V. Univ Sao Paulo Engn Sch Sao Carlos Dept Mech Engn BR-13566590 Sao Paulo Brazil

ISBN: (纸本)9781424448081

This project aims to apply image processing techniques in computer vision featuring an omnidirectional vision system to agricultural mobile robots (AMR) used for trajectory navigation problems, as well as localization matters. To carry through this task, computational methods based on the JSEG algorithm were used to provide the classification and the characterization of such problems, together with Artificial Neural Networks (ANN) for pattern recognition. Therefore, it was possible to run simulations and carry out analyses of the performance of JSEG image segmentation technique through Matlab/Octave platforms, along with the application of customized Back-propagation algorithm and statistical methods in a Simulink environment. Having the aforementioned procedures been done, it was practicable to classify and also characterize the HSV space color segments, not to mention allow the recognition of patterns in which reasonably accurate results were obtained.

关键词： image processing image segmentation mobile robots computer vision

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A solution for eigen fuzzy sets of adjoint max-min composition and its application to image analysis 3

A solution for eigen fuzzy sets of adjoint max-min compositi...

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3rd ieee International symposium on Intelligent signal processing, WISP 2003

作者： Nobuhara, Hajime Hirota, Kaoru Department of Computational Intelligence and Systems Science Tokyo Institute of Technology 4259 Nagatsuta Midiri-ku Yokohama226-8502 Japan

ISBN: (纸本)0780378644

As a principal component analysis of the images based on an ordered structure, the greatest eigen fuzzy set (GEFS) and the smallest eigen fuzzy set (SEFS) of max-min composition and adjoint one, are proposed. In the case of the proposed method, an original image can be regarded as a fuzzy relation by intensity normalization, and the GEFS and the SEFS are obtained as the transitive closure of the fuzzy relation. Through experiments using 91 test images extracted from 'View Sphere Database', it is confirmed that the GEFS and SEFS can be obtained during 10 iterations, under the condition that the size of the original image is 256 × 256 pixels. ©2003 ieee.

关键词： image analysis

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Sparse Subspace Clustering for Hyperspectral images with Missing Pixels 22

Sparse Subspace Clustering for Hyperspectral Images with Mis...

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22nd symposium on image, signal processing and Artificial Vision (STSIVA)

作者： Bacca, Jorge Sanchez, Karen Arguello, Henry Univ Ind Santander Dept Comp Sci Bucaramanga Colombia Univ Ind Santander Dept Elect Engn Bucaramanga Colombia

ISBN: (纸本)9781728114910

Spectral image clustering discovers groups and identifies distributions from spectral signatures without requiring a previous training stage. The sparse subspace clustering-based methods group spectral signatures in different subspaces, finding the sparsest representation for each pixel, guaranteeing that they belong to the same class. Although these methods have shown good accuracy, as the number of pixels increases, computational complexity becomes intractable. This paper proposes to reduce the number of pixels to be classified in the spectral image by half through a sub-sampling procedure that eliminate every two contiguous pixels, preserving the spatial structure of the image. Then, the clustering result is obtained using its spatial information. The performance of the proposed spectral image clustering framework is evaluated in three datasets showing that similar accuracy is obtained up to 7.9 times faster compared to the classification of the data sets without subsampling.

关键词： Spectral images Spectral clustering Sparse Subspace Clustering Sub-sampling image Classification

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