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An ant colony optimization routing algorithm for two order pickers with congestion consideration

Computers & Industrial Engineering 2013年第1期66卷 77-85页

作者： Fangyu Chen Hongwei Wang Chao Qi Yong Xie Key Laboratory of Image Processing and Intelligent Control Institute of Systems Engineering Huazhong University of Science & Technology Hubei Wuhan 430074 People’s Republic of China

This paper develops a routing method to control the picker congestion that challenges the traditional assumption regarding the narrow-aisle order picking system. We proposes a new routing algorithm based on Ant Colony Optimization (ACO) for two order pickers (A-TOP) with congestion consideration. Using two extended dedicated heuristics with congestion consideration as reference group, a comprehensive simulation study is conducted to evaluate the effectiveness of A-TOP. The simulation proves that A-TOP achieves the shortest total picking time in most instances and performs well in dealing with the congestion. The impacts of warehouse layout, order size, and pick:walk-time ratio on A-TOP and system performance are analyzed as well. A-TOP can adapt to different warehouse configurations, meanwhile, it can be easily extended to the situation with more than two order pickers.

关键词： Routing method Order picking Ant colony optimization Congestion Warehouse management

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WAVELENGTH-ADAPTIVE image FORMATION MODEL AND GEOMETRIC CLASSIFICATION FOR DEFOGGING UNMANNED AERIAL VEHICLE imageS

WAVELENGTH-ADAPTIVE IMAGE FORMATION MODEL AND GEOMETRIC CLAS...

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IEEE International Conference on Acoustics, Speech, and Signal processing

作者： Inhye Yoon Monson H. Hayes Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea

ISBN: (纸本)9781479903573

In this paper, we present an image enhancement algorithm based on the wavelength-adaptive image formation model and geometric classification for defogging UAV images. We first generate a labeled image using geometric class-based segmentation. We then generate a modified transmission map based on the wavelength-adaptive image formation model with scattering coefficients in the labeled image. We also estimate the atmospheric light from the modified transmission map instead of simply choosing the brightest pixel. The proposed method can significantly enhance the visibility of foggy UAV images compared with existing monochrome model-based defogging method. The proposed algorithm can enhance the visibility by removing atmospheric degradation factor in airborne images acquired by aerial platforms such as satellite, airplane, and UAV under critical weather conditions such as haze, fog, and smoke.

关键词： image enhancement image defogging unmanned aerial vehicle image enhancement images drone honey bees Unmanned Aerial Vehicle vehicle image enhancement algorithm image formation aerial platforms UNMANNED visibility ANTENNA Scattering coefficient BRIGHT

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Single image-based depth estimation using dual off-axis color filtered aperture camera

Single image-based depth estimation using dual off-axis colo...

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International Conference on Acoustics, Speech, and Signal processing (ICASSP)

作者： Seungwon Lee Nahyun Kim Kyungwon Jung Monson H. Hayes Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul South Korea

ISBN: (纸本)9781479903573

In this paper, we present a dual off-axis color filtered aperture (DCA)-based computational imaging system for depth estimation in a single-camera framework. The DCA has one primary (red) color and its complementary (cyan) color filtered apertures located off the optical axis to generate misalignment between color channels depending on the distance of a region-of-interest from the camera. Disparity of color shifting values (CSVs) between color channels in the image acquired by the DCA-based imaging system is estimated using L 1 -norm minimization of energy functional considering both brightness and gradient constancies and only translation of x-axis. The two data terms both red to green (R-G) and red to blue (R-B) are combined in a single data term. The proposed imaging system can be implemented by simply inserting an appropriately resized DCA into any general optical system. Experimental results show that the proposed DCA can estimate the distance of the scene from the camera in the single-camera framework.

关键词： image color analysis Cameras Apertures Estimation Optical imaging Channel estimation

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An ontology-based emergency domain knowledge model for HTN planning

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IFAC Proceedings Volumes 2013年第13期46卷 377-382页

作者： Dian Liu Hong-wei Wang Kuang-yu Liu Jian Wang Institute of Systems Engineering Huazhong University of Science and Technology P.R.China 430074 Key Laboratory of Education Ministry of Image processing and Intelligent Control Huazhong University of Science and Technology P.R. China 430074 (Tel: *** ) Key Laboratory of Education Ministry of Image processing and Intelligent Control Huazhong University of Science and Technology P.R. China 430074 (Tel: ***

Hierarchy task network (HTN) planning, as one of AI planning approaches, has been widely used in the emergency decision making for action planning in recent years, in which domain knowledge plays an important role. The special and complicated characteristics of emergency domain knowledge make it difficult to model, hindering the application of HTN planning to emergency action plan development. Though ontology modeling can get over the difficulty, existing ontology models for the emergency domain knowledge are either incomplete or not applicable for HTN planning. This paper aims at constructing emergency domain knowledge ontology applicable for HTN planner SHOP2 which can effectively support the emergency action plan development. An approach of translating an emergency domain knowledge model into a SHOP2 domain is also discussed in the paper. Finally an implementation of our work is roughly introduced.

关键词： Emergency action plan development HTN planning SHOP2 emergency domain knowledge ontology translation

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DARK CHANNEL PRIOR-BASED SPATIALLY ADAPTIVE CONTRAST ENHANCEMENT FOR BACK LIGHTING COMPENSATION

DARK CHANNEL PRIOR-BASED SPATIALLY ADAPTIVE CONTRAST ENHANCE...

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IEEE International Conference on Acoustics, Speech, and Signal processing

作者： Jaehyun Im Inhye Yoon Monson H. Hayes Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul 156-756 Korea

ISBN: (纸本)9781479903573

In this paper, we present a novel contrast enhancement method for backlit images that consists of three steps: i) computation of the transmission coefficients using the dark channel prior, ii) generation of multiple images having different exposures based on the transmission coefficients, and iii) image fusion. Compared to global intensity transformation methods and spatially invariant contrast enhancement algorithms, our approach first extracts under-exposed regions using the dark channel prior map, and then performs spatially adaptive contrast enhancement. As a result, the contrast of the image is increased, especially for backlit scenes and those with very wide dynamic range, while still preserving image details and color.

关键词： contrast enhancement contrast enhancement method TRANSMISSION COEFFICIENT Lighting Backlights image CONTRAST multiple image compensated images wide dynamic range imagery (Psychotherapy)

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The impact of stock-dependent demand on supply chain dynamics

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Applied Mathematical Modelling 2013年第18-19期37卷 8348-8362页

作者： Yongchang Wei Hongwei Wang Chao Qi Institute of Systems Engineering and the Key Laboratory of Image Processing and Intelligent Control of Education Ministry Huazhong University of Science and Technology Wuhan 430074 PR China School of Business Administration Zhongnan University of Economics and Law Wuhan 430073 PR China

This paper presents an investigation on the dynamics of a supply chain system under stock-dependent demand. Considering the feature of piecewise linearity, a switched linear model composed of three subsystems is developed. Based on the switched model, some analytical stability results are derived. Simulation experiments are designed to verify the stability results and observe nonlinear dynamics. We show that stock-dependent demand not only leads to different stability results but also makes nonlinear dynamics more complicated. We also reveal that the nonlinear dynamics of the switched model, such as chaotic and periodic fluctuations of inventory and order, are essentially caused by switching frequently among subsystems due to uncertainties of inventory status. The results obtained in this paper help us understand the dynamic complexities of supply chain system and provide guidelines for selecting decision parameters to improve overall performance.

关键词： Supply chain system Stock-dependent demand Dynamics Switched system Modeling and simulation

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COMPRESSIVE SENSING-BASED image DENOISING USING ADAPTIVE MULTIPLE SAMPLING AND OPTIMAL ERROR TOLERANCE

COMPRESSIVE SENSING-BASED IMAGE DENOISING USING ADAPTIVE MUL...

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IEEE International Conference on Acoustics, Speech, and Signal processing

作者： Wonseok Kang Eunsung Lee Eunjung Chea Aggelos K. Katsaggelos Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Seoul Chung-Ang University Korea Department of Electrical Engineering and Computer Science Northwestern University Evanston IL 60208 USA

ISBN: (纸本)9781479903573

In this paper, we present a compressive sensing-based image denoising algorithm using spatially adaptive image representation and estimation of optimal error tolerance based on sparse signal analysis. The proposed method performs block-based multiple compressive sampling after decomposing the sparse signal into feature and non-feature regions using simple statistical analysis. For minimization of recovery error and number of iterations, the modified OMP method estimates the optimal error tolerance using the average variance in the recovery step. Experimental results demonstrate that the proposed denoising algorithm better removes noise without undesired artifacts than existing state-of-the-art methods in terms of both objective (PSNR/SSIM) and subjective measures. processing time of the proposed method is 5 to 10 times faster than the standard OMP-based method.

关键词： Tolerances physiologic tolerance Sampling system recovery image denoising image representation images Signal analysis Statistical analysis Statistical methods image denoising algorithm

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Adaptively partitioned block-based backlit image enhancement for consumer mobile devices

Adaptively partitioned block-based backlit image enhancement...

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IEEE International Conference on Consumer Electronics (ICCE)

作者： Nahyun Kim Seungwon Lee Ewoo Chon Monson H. Hayes Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University (CAU) Seoul South Korea 1st Research and Development Center/CP group Nextchip Company Limited Seoul South Korea

In this paper, we present an efficient backlit region detection and enhancement method with low-computational cost for consumer mobile imaging devices. The proposed approach partitions an input image into multiple rectangular blocks, and uses a fuzzy logic-based optimal threshold to classify each block as backlit, background, or ambiguous. Backlit blocks are then processed using a contrast enhancement algorithm, whereas those block that are classified as ambiguous are further partitioned into four subblocks, and each subblock goes through further classification. The major advantage of the proposed method is computational efficiency and improved quality with minimized blocking artifacts compared with other block-based approaches.

关键词： Classification algorithms Partitioning algorithms image enhancement Algorithm design and analysis Histograms Imaging Mobile communication

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REAL-TIME SUPER-RESOLUTION FOR DIGITAL ZOOMING USING FINITE KERNEL-BASED EDGE ORIENTATION ESTIMATION AND TRUNCATED image RESTORATION

REAL-TIME SUPER-RESOLUTION FOR DIGITAL ZOOMING USING FINITE ...

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IEEE International Conference on image processing

作者： Wonseok Kang Jaehwan Jeon Eunsung Lee Changhun Cho Junghoon Jung Taechan Kim Aggelos K. Katsaggelos Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea System LSI Samsung Electronics Co. Ltd Suwon Korea Department of Electrical Engineering and Computer Science Northwestern University Evanston IL 60208 USA

ISBN: (纸本)9781479923427

This paper presents a novel real-time super-resolution (SR) method using directionally adaptive image interpolation and image restoration. The proposed interpolation method estimates the edge orientation using steerable filters and performs edge refinement along the estimated edge orientation. Bi-linear and bi-cubic interpolation filters are then selectively used according to the estimated edge orientation for reducing jagging artifacts in slanting edge regions. The proposed restoration method can effectively remove image degradation caused by interpolation using the directionally adaptive truncated constrained least-squares (TCLS) filter. The proposed method provides high-quality magnified images which are similar to or better than the result of advanced interpolation or SR methods without high computational load. Experimental results indicate that the proposed system gives higher peak-to-peak signal-to-noise ratio (PSNR) and structural similarity (SSIM) values than the state-of-the-art image interpolation methods.

关键词： Super-resolution image interpolation image restoration digital zooming

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FREQUENCY-DOMAIN ANALYSIS OF DISCRETE WAVELET TRANSFORM COEFFICIENTS AND THEIR ADAPTIVE SHRINKAGE FOR ANTI-ALIASING

FREQUENCY-DOMAIN ANALYSIS OF DISCRETE WAVELET TRANSFORM COEF...

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IEEE International Conference on image processing

作者： Eunjung Chae Eunsung Lee Wonseok Kang Younghoon Lim Junghoon Jung Taechan Kim Aggelos K. Katsaggelos Joonki Paik Image Processing and Intelligent Systems Laboratory Graduate School of Advanced Imaging Science Multimedia and Film Chung-Ang University Seoul Korea System LSI Samsung Electronics Co. Ltd Suwon Korea Department of Electrical Engineering and Computer Science Northwestern University Evanston IL 60208 USA

ISBN: (纸本)9781479923427

We present an antialiasing method using combined wavelet-Fourier transform and spatially adaptive shrinkage of the transform coefficients. Traditional antialiasing methods employ a simple low-pass filter onto the entire image, so the resulting image loses not only aliasing artifacts but also high-frequency components such as edges and ridges. The proposed algorithm analyzes the property of the LL subband of the discrete wavelet transform (DWT), and reduces aliasing artifacts using patch-adaptive shrinkage of the DWT coefficients. More specifically, an antialiased LL subband is obtained using adaptive patch-based aliasing reduction. To detect an aliased region, we subtract the discrete Fourier transform (DFT) coefficients of the LL subband from the DFT coefficients of antialiased LL subband. The detected aliasing artifacts in the LH, HL, and HH subbands are reduced by patch-wise adaptive shrinkage of the transform coefficients. The resulting antialiased image is obtained using the inverse DWT. The aliasing artifacts can be efficiently reduced by adaptively shrinking wavelet transform coefficients for preserving high-frequency image details. The proposed antialiasing algorithm is suitable for removing aliasing artifacts which frequently occur in imaging sensors with limited resolution.

关键词： Anti-aliasing wavelet-Fourier transform image enhancement patch-adaptive shrinkage antialiasing image enhancement Aliasing shrinkage Artifacts subband domain analysis Coefficients Sensors (image) Frequency-domain analysis discrete Fourier transform

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