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Inshore ship Object Detection and Recognition using Hybrid Combination Algorithm using MATLAB

Inshore ship Object Detection and Recognition using Hybrid C...

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International conference on Wireless Communications, signal processing and Networking

作者： Gaurav Soni V. K. Banga Armanpreet Singh Department of Electronics & Communication Engineering Amritsar College of engineering & Technology Punjab India Amritsar College of engineering & Technology Punjab India Amritsar College of Engineering & Technology Punjab India

ISBN: (纸本)9781467393393

In this simulation study, the proposed Inshore object detection model has been investigated to detect the objects in the oceanic images in order to reduce the human effort to shortlist the images containing the useful information. The simulative analysis focus on the design and implementation to use the hybrid combination of the color and shape based analysis to detect the objects precisely. The MATLAB based simulation is performed on various kinds of images obtained from satellite, and the performance investigation has been performed on the basis of various performance parameters. The aim of the proposed model is helping the rescue operations by creating the shortlisted oceanographic imagery data containing the useful objects, in order to match the required object defined in the visible template.

关键词： Feature detection Oceanography Oceanic image processing Object detection Object classification Object recognition

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Coupled dictionary learning for multimodal image super-resolution

Coupled dictionary learning for multimodal image super-resol...

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IEEE Global conference on signal and Information processing (GlobalSIP)

作者： Pingfan Song João F. C. Mota Nikos Deligiannis Miguel R. D. Rodrigues Department of Electronic and Electrical Engineering University College London UK iMinds vzw Ghent Belgium Department of Electronics and Informatics Vrije Universiteit Brussel Belgium

Real-world data processing problems often involve multiple data modalities, e.g., panchromatic and multispectral images, positron emission tomography (PET) and magnetic resonance imaging (MRI) images. As these modalities capture information associated with the same phenomenon, they must necessarily be correlated, although the precise relation is rarely known. In this paper, we propose a coupled dictionary learning (CDL) framework to automatically learn these relations. In particular, we propose a new data model to characterize both similarities and discrepancies between multimodal signals in terms of common and unique sparse representations with respect to a group of coupled dictionaries. However, learning these coupled dictionaries involves solving a highly non-convex structural dictionary learning problem. To address this problem, we design a coupled dictionary learning algorithm, referred to sequential recursive optimization (SRO) algorithm, to sequentially learn these dictionaries in a recursive manner. By capitalizing on our model and algorithm, we conceive a CDL based multimodal image super-resolution (SR) approach. Practical multispectral image SR experiments demonstrate that our SR approach outperforms the bicubic interpolation and the state-of-the-art dictionary learning based image SR approach, with Peak-SNR (PSNR) gains of up to 8.2 dB and 5.1 dB, respectively.

关键词： Dictionaries image resolution signal resolution Data models Training Optimization Sparse matrices

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Vision-based decision tree controller design method sensorless application by using angle knowledge

Vision-based decision tree controller design method sensorle...

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IEEE signal processing and Communications Applications (SIU)

作者： Mahmut Dirik Adnan Fatih Kocamaz Emrah Dönmez Inonu Universitesi Malatya Malatya TR

In this study, a new control model for differential drive mobile robots was developed by using image-based decision tree method(DTM). Developed mobile robot control model was designed in an obstacle-free environment. The wheel encoder sensor was designed as a controller capable of independent positioning by using real-time images from overhead cameras on the bird's eye view. In this new method, a virtual triangular area between the target and the robot was created. These triangular base angles were calculated on the image. Decision tree controller was determined as the difference between the base angles by branching. Decision Tree leaves control determines the left and right wheel speeds depending on the difference model design was carried out. The developed new controller model was tested on Khepera IV robot. In practice, the robot's speed and angle of the body was carried uncensored control and it was observed to find the target in different applications. Application of the results and performance of the system was shown.

关键词： Mobile robots Decision trees Cameras Robot vision systems Pulse width modulation

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image-based clustering analysis of massive vehicle networking data

Image-based clustering analysis of massive vehicle networkin...

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International conference on Wireless Communications and signal processing (WCSP)

作者： Zhonghui Chen Zhipeng Xie Xinxin Feng College of Physics and Information Engineering Fuzhou University Fuzhou China

ISBN: (纸本)9781509028610

In order to make full use of the massive vehicle networking data and dig out the characteristics of the vehicle driving behaviors, the analysis of the massive vehicle networking data is indispensable. And clustering analysis is an effective way to extract the information which can guide and supervise the vehicles. In this paper, we propose a novel initial clustering center selection algorithm based on the image recognition. In addition, in order to shorter the time of the clustering algorithm, we improve the ε-Link based on the massive vehicle networking data. We refer to image-based clustering algorithm applied on matching map of the vehicle networking data and ultimately obtain the traffic hot spot map of the urban roads by the clustering analysis. We evaluate our algorithm by doing thorough simulation on the massive data of vehicles in Fuzhou city. The result shows that when compared to the traditional clustering algorithms with great randomness in selection, the image-based clustering algorithm consumes less time in the case of massive vehicle networking data. And through the analysis of the trajectory data, the traffic hot spot map can be formed and practically reflects the practical traffic flow of Fuzhou city.

关键词： Vehicles Roads Clustering algorithms Algorithm design and analysis Urban areas Trajectory Approximation algorithms

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image reconstruction from discrete orthogonal Racah moments

Image reconstruction from discrete orthogonal Racah moments

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Canadian conference on Electrical and Computer Engineering (CCECE)

作者： Yexiao Wu Simon Liao Applied Computer Science The University of Winnipeg Winnipeg Manitoba

ISBN: (纸本)9781467387224

In this research, a matrix notation method to extract discrete orthogonal Racah moments is proposed to reduce the computation time. To verify this new computational method, the image reconstructions from higher orders of Racah moments are performed. Our experimental results show that the Racah moments computing time has been reduced tremendously, while the testing image can be reconstructed completely by Racah moments of orders up to 510 without any error.

关键词： image reconstruction Testing Algorithm design and analysis signal processing algorithms Pattern recognition Real-time systems

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FISHEYE VIDEO CODING USING ELASTIC MOTION COMPENSATED REFERENCE FRAMES

FISHEYE VIDEO CODING USING ELASTIC MOTION COMPENSATED REFERE...

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IEEE International conference on image processing

作者： Ashek Ahmmed Miska M. Hannuksela Moncef Gabbouj Department of Signal Processing Tampere University of Technology Tampere Finland Nokia Technologies Tampere Finland

ISBN: (纸本)9781467399623

Fisheye cameras have become extremely popular in applications where the goal is to capture large fields of view with only one camera. However, the wide-angle fisheye imagery has special characteristics that may not be very well suited for modern video codecs that employ block-based translational motion model. This model fails to describe complex deformable motion which is often present in fisheye videos. In this paper, we advocate for the usage of elastic motion model in compensating such a complex motion. The presented design enables the re-use of existing codecs, such as HEVC, without modifications in low-level coding tools. Experimental results show that a savings in bit rate of up to 6.54% is achievable over standalone HEVC if the elastic motion compensated prediction is used as an additional reference frame.

关键词： Solid modeling Cameras Bit rate Video sequences Video coding Encoding Deformable models

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A divide-and-conquer dictionary learning algorithm and its performance analysis

A divide-and-conquer dictionary learning algorithm and its p...

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International conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Subhadip Mukherjee Chandra Sekhar Seelamantula Department of Electrical Engineering Indian Institute of Science Bangalore India

ISBN: (纸本)9781479999897

We address the problem of learning a sparsifying synthesis dictionary over large datasets that occur in numerous signal and image processing applications, such as inpainting, super-resolution, etc. We develop a dictionary learning algorithm that exploits the similarity of the training examples to reduce the training time. Training datasets containing correlated examples typically occur in image processing applications, as the datasets contain the patches extracted from natural images as training vectors. Our algorithm employs a divide- and-conquer approach, where one leverages the correlation within the training examples to segment the dataset into clusters containing similar examples, and learn local dictionaries for each of them. This constitutes the divide step of the algorithm. In the conquer step, a global dictionary is trained using the atoms of the local dictionaries as the training examples. We analyze the run-time complexity and the representation error of the proposed divide-and-conquer dictionary learning algorithm, and compare the performance with the batch and online dictionary learning algorithms, both on synthesized dataset and natural images. The analysis reveals that the proposed algorithm has an asymptotic complexity that is linear and logarithmic in the number of training examples, corresponding to sequential and parallel implementations, respectively.

关键词： Dictionaries Training Complexity theory Clustering algorithms Algorithm design and analysis Correlation Encoding

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design of Carrier Tracking Loop in Satellite Navigation Receiver Based on High-Order Doppler Parameter Detection Algorithm

Design of Carrier Tracking Loop in Satellite Navigation Rece...

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International conference on Multimedia and image processing (ICMIP)

作者： Jinan Han Chaozhu Zhang Malek Karaim College of Information and Communication Engineering Harbin Engineering University Harbin China Electrical and Computer Engineering Department Queens University Kingston ON Canada

ISBN: (纸本)9781467389419

To improve the tracking performance of global positioning system receivers, we have proposed a carrier loop structure based on a high-order Doppler parameter detection algorithm. Applied when the input of the tracking loop is the carrier signal, this solution begins by establishing a relationship between the first and second order rate of change of the Doppler frequency shift and the output of the discriminator, after which the Doppler frequency shift can be estimated. Following this, we used the combined frequency-lock loop and phase-lock loop methods to build a carrier loop structure for the high-order Doppler parameter detection algorithm. Our results showed that the proposed carrier loop structure performs well in high-dynamic conditions compared with other carrier loop structures. Accordingly, the structure provides an improved design for the tracking module of satellite navigation receivers.

关键词： Doppler effect Frequency locked loops Phase locked loops Frequency estimation Time-frequency analysis Tracking loops Receivers

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Analysis Dictionary Learning Based on Max Transvection Function

Analysis Dictionary Learning Based on Max Transvection Funct...

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2016 IEEE International conference on signal and image processing

作者： Haolong Wang Wanting Fang Wenwu Wang Ye Zhang Saeid Sanei Department of Electronic and Information Engineering Nanchang University Centre for Vision Speech and Signal Processing University of Surrey Departme of Computing University of Surrey

Analysis dictionary learning(ADL) aims to design dictionaries from training data based on an analysis sparse representation *** analysis model is an alternative model to the sparse synthesis model used in a variety of signal processing *** paper introduces a new ADL method called MAX-ADL algorithm used to estimate the dictionary directly from the noisy *** algorithm employs MAX transvection function instead of ?1-norm to construct the objective function, and then the analysis dictionary can be obtained by using a gradient method to iteratively optimize the objective *** results show that the algorithm performs well in natural image denoising.

关键词： analysis sparsity analysis dictionary learning image denoising MAX transvection function

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Colour-texture image segmentation based on graph cut using student's t distribution

Colour-texture image segmentation based on graph cut using s...

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International conference on Inventive Computation Technologies (ICICT)

作者： Sonali Warudkar S. R. Kinge M. T. Kolte Department of ENTC Maeer's Mitcoe Kothrud Pune MH India

ISBN: (纸本)9781509012862

image segmentation for analysis is a major aspect of perception and till date it is challenging issue for machine perception. Many years of study in computer vision prove that segmenting an image into meaningful regions for subsequent processing (e.g., pattern recognition) is just as hard problem as invariant pattern recognition. In this paper, the proposed work uses the different type of procedures has been followed to carry out colour-texture image segmentation. Segmentation methods are designed to integrate more feature information, with high accuracy and satisfactory visual entirety. The segmentation process is based on MSST and student's t-distribution method.

关键词： image segmentation image color analysis signal processing algorithms Nonhomogeneous media Tensile stress Algorithm design and analysis Filtering

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