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Visual simulation method for installation of wayside facilities using video sequences

Quarterly Report of RTRI (Railway Technical Research Institute) 2016年第4期57卷 280-286页

作者： Nagamine, Nozomi Nakasone, Ryuta Ukai, Masato Signalling Systems Laboratory Signalling and Transport Information Technology Division Japan

This research aims to create a simulator that would generate simulated images for use when investigating where to install wayside signals along a railway track. A simulation method has been developed, whereby the virtual line of sight of the driver with respect to way-side signals on a track is displayed by using the images of signals overlaid onto the view from the front of the train. By means of this simulation technique, the time needed for the study of on-site wayside signal positioning can be cut without imposing restrictions on train schedules or operations. This report describes the algorithms applied and explains the verifications made using test data.

关键词： image processing

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Shadow lane robust detection by image signal local reconstruction

International Journal of Signal Processing, Image Processing...

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International Journal of Signal processing, image processing and Pattern Recognition 2016年第3期9卷 89-102页

作者： Du, Mingfang Junzheng, Wang Nan, Li Duoyang, Li School of Automation Beijing Union University Beijing China State Key Laboratory of Complex System Intelligent Control and Decision Beijing Institute of Technology Beijing China Beijing Key Laboratory of Information Service Engineering

In order to resolve shadow interference and slow image processing speed in the visual navigation of unmanned vehicles on city roads, a new lane detection algorithm based on the Inverse Perspective Mapping(IPM) of vertical sub-image reconstruction using local bands was proposed. The lane’s IPM aerial image was obtained using the projective transformation of three-dimensional images of city roads. The ROI portion of the IPM map was decomposed and analyzed using the sym3 wavelet, and after analyzing and comparing the experimental results the first and second levels of the vertical sub images were selected for the reconstruction, compression, and removal of shadows from the original image. The Canny algorithm was proposed and adopted in order to extract the edge features of the reconstructed images according to real-time road image quality. A modified, polar angle, constraint-based, fast Hough transform was used to locate the candidate lanes. Finally, the main control point, straight-line-fitting algorithm was used to fit the final lanes, which achieved the precise location and recognition of the lane lines. The California Polytechnic lane data set, a public data platform, which is now widely used in road visual recognition fields around the world, was selected for the testing and verification of the algorithm. The results of the experiment and actual operation indicated that, despite having a storage space of approximately one tenth the size of similar algorithms, this detection algorithm effectively solves the issue of shadow removal, meets the real-time requirements of roadway image processing systems for unmanned vehicles with a recognition time of less than 20ms, and is robust. © 2016 SERSC.

关键词： Wavelet transforms

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Comparative performance study of word segmentation techniques for handwritten odia documents

Comparative performance study of word segmentation technique...

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International Conference on Signal processing, Communication, Power and Embedded System (SCOPES)

作者： Ayush Pradhan Sidharth Behera Ganapati Panda Babita Majhi Computer Science Engineering National Institute of Technology Rourkela School of Electrical and Computer Engineering Indian Institute of Technology Bhubaneswar Department of Computer Science and IT Central University Bilaspur India

ISBN: (纸本)9781509046218

Word segmentation of handwritten documents is a vital step in the Optical Character Recognition system as its accuracy greatly influences the overall recognition performance. In the literature, various methods have been proposed for word segmentation of handwritten documents of various languages. However, it is observed that for Odia, which is an important Indian language, very little work has been reported on word segmentation. Hence, the objective of this paper is to employ two standard existing methods to segment words of Odia handwritten documents and compare the segmentation performance of these methods with the lone Water Reservoir Algorithm available in the literature and finally rank those methods based on their segmentation performance. It is observed that out of three methods, the Tree Structure method performs the best comparing four different performance measures.

关键词： Signal processing algorithms image segmentation Character recognition Reservoirs Signal processing Embedded systems

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Night-time vehicle detection using low exposure video enhancement and lamp detection

Night-time vehicle detection using low exposure video enhanc...

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International Conference on Electronics, Information and Communications (ICEIC)

作者： Jin-Woo Park Byung Cheol Song Department of Electronic Engineering Inha University Incheon Republic of Korea

ISBN: (纸本)9781467380171

This paper proposes a vehicle detection algorithm using pre-processing and lamp detection at night-time. First, we present a vehicle detection using contrast enhancement. By applying a specific contrast enhancement to night-time images with low exposure, we can enhance salient features even at dark night-time. Next, we detect a pair of rear lamps from the pre-processed image(s). Finally, we can find forward vehicle(s) by lamp pairing. Experimental results show that the proposed algorithm provides reliable detection accuracy.

关键词： Vehicle detection Vehicles Classification algorithms image color analysis Training Advanced driver assistance systems Computer vision

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Massive graph processing on nanocomputers

Massive graph processing on nanocomputers

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IEEE International Conference on Big Data

作者： Bryan Rainey David F. Gleich Department of Computer Science Purdue University West Lafayette Indiana

ISBN: (纸本)9781467390064

Many recently proposed graph-processing frameworks utilize powerful computer clusters with dozens of cores to process massive graphs. Their usability and flexibility often come at a cost. We demonstrate that custom software written for “nanocomputers,” including a credit-card-sized Raspberry Pi, a low-cost ARM server, and an Intel Atom computer, can process the same graphs. Our implementations of PageRank and connected components stream graphs from external storage while performing computation in the limited main memory on these nanocomputers. The results show that a $100 computer with an Intel Atom core can compute PageRank and connected components on a 1.5-billion-edge Twitter graph as quickly as graph-processing systems running on machines with up to 48 cores. As people continue to apply graph computations to large datasets, this research suggests that there may be cost and energy advantages to using nanocomputers.

关键词： Computers Program processors Convergence Hardware Approximation algorithms image edge detection Standards

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A finger vein recognition system

A finger vein recognition system

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Conference on Advances in Signal processing (CASP)

作者： Manisha Sapkale S. M. Rajbhoj Department of Electronics & Telecommunication Savitribai Phule Pune University

ISBN: (纸本)9781509008506

The most vital requirement in today's world of spoofing attacks is the high security. The development in consumer electronics demands for high security with high accuracy and high speed of authentication. Human behavioural and physiological features in biometrics has the large scope as a solution for security issues. However, the existing biometric systems are highly complex in terms of time or space or both, and thus not suitable in very high security. Thus an embedded finger-vein recognition system for authentication is proposed. The system is to be implemented using novel finger vein recognition algorithm and lacunae, fractal dimension and gabor filter are the algorithms used for feature extraction and the matching of the extracted feature is done using the distance classifier. The analysis is done using the various features from which the kurtosis, range shows large variation from person to person. Based on this analysis finger vein recognition becomes easier and reliable.

关键词： Veins Fractals Feature extraction Fingers Biometrics (access control) Security image recognition

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Estimation of Measurement of Distance to the Object by Analyzing the Blur of Its image Series

Estimation of Measurement of Distance to the Object by Analy...

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International Siberian Conference on Control and Communications

作者： Daniil A. Loktev Alexey A. Loktev Department of Information Systems and Telecommunications Bauman Moscow State Technical University Moscow Russia Department of Transport Construction Moscow State University of Railway Engineering Moscow Russia

ISBN: (纸本)9781467383844

An important element of the modern automated control systems, monitoring and remote access is to obtain primary information about the state and behavior of static or moving objects. To obtain such information we propose to use photo and video detectors, which could provide images of objects with high resolution in the system. Thus, the possibility of determining the geometric and kinematic parameters of the moving object are significantly reduced because of the different aspects of producing an image, one of these aspects is the blur. The geometric parameters of the object are determined by analyzing the blur of its images obtained at different settings of the photodetector. In this paper, algorithms of processing of primary information are improved by the use of methods and procedures of statistical analysis and probabilistic approach. It increases the accuracy of determined characteristics, the applicability of procedures for the calculation of state parameters (size, shape, distance from observer) and behavior parameters of the object (speed and direction) and reduces the computational complexity of the final algorithm. The research allows not only determine the geometric parameters of the object, but also to evaluate their accuracy and to develop elements of the algorithm that can be used in real systems of video monitoring

关键词： image blur video monitoring system method of least squares method of least modules object geometric parameters Bayesian estimation loss function distribution function of errors

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Exploiting approximate adder circuits for power-efficient Gaussian and Gradient filters for Canny edge detector algorithm

Exploiting approximate adder circuits for power-efficient Ga...

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IEEE Latin American Symposium on Circuits and systems (LASCAS)

作者： Julio de Oliveira Leonardo Soares Eduardo Costa Sergio Bampi Graduate Program on Electronic Engineering and Computing Catholic University of Pelotas (UCPel) Pelotas Brazil Graduare Program on Microelectronics (PGMicro) Federal University of Rio Grande do Sul (UFRGS) Porto Alegre Brazil

This paper proposes the exploration of approximate adders for the implementation of power-efficient Gaussian and Gradient filters for image processing. The Gaussian filter is a convolution operator which is used to blur images and to remove noise. On the other hand, the Gradient of an image measures how it is changing. Both blocks can be designed in hardware using only shifts and additions. In this work we exploit a set of approximate adders in order to implement energy-efficient filters. The tree of adders of Gaussian and Gradient filters are implemented using one RCA-based approximate adder, as well as an Error-Tolerant Adder ETAI. The approximate architectures are compared to the best precise implementation of the filters. As the Gaussian and Gradient blocks are part of the Canny edge detector algorithm, we have implemented the adder trees of the filters aiming this application. Our main results show that for an efficient power realization of this algorithm, the best strategy consists in the implementation of the Gaussian filter with ETA I adder, and the Gradient filter with the RCA-based adder.

关键词： Adders Filtering algorithms image edge detection Computer architecture Detectors Kernel

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An application of the supervoxel-based Fuzzy C-Means with a GPU support to segmentation of volumetric brain images

An application of the supervoxel-based Fuzzy C-Means with a ...

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Federated Conference on Computer Science and Information systems (FedCSIS)

作者： Anna Fabijańska Jarosław Gocławski Lodz University of Technology Institute of Applied Computer Science Lodz Poland

In this paper the problem of segmentation of volumetric medical images is considered. The fast and effective segmentation is obtained by applying the proposed approach which combines the idea of supervoxels and the Fuzzy C-Means algorithm. In particular, Fuzzy C-Means is used to cluster supervoxels produced by the fast 3D region growing. Additional acceleration of the method is achieved with the support of graphical processor (GPU). The detailed description of the proposed approach is given. The results of applying the method to volumetric CT and MRI brain images and CT images of various phantoms are presented, analysed and discussed. The issues related to accuracy of the method, memory workload and the running time are also considered.

关键词： Graphics processing units image segmentation Computed tomography Magnetic resonance imaging Kernel Brain Clustering algorithms

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Analyzing images in frequency domain to estimate the quality of wood particles in OSB production

Analyzing images in frequency domain to estimate the quality...

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IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement systems and Applications

作者： Ruggero Donida Labati Angelo Genovese Enrique Muñoz Vincenzo Piuri Fabio Scotti Gianluca Sforza Department of Computer Science Università degli Studi di Milano Italy

The analysis of the quality of particulate materials is of great importance for a variety of research and industrial applications. Most image-based methods rely on the segmentation of the image to measure the particles and aggregate their characteristics. However, the segmentation of particulate materials can be severely affected when the setup is not controlled. For instance, when there are device errors, changes in the light conditions, or when the camera gets dirty because of the dust or a similar substance. All of these circumstances are common in industrial setups, like the one studied in this paper. This work presents a framework for quality estimation based on image processing algorithms that avoids segmentation. The considered application scenario is the online quality control of the production of Oriented Strand Boards (OSB), a type of wood panel frequently used in construction and manufacturing industries. The proposed method quantizes frequency domain into a histogram using a non-parametric method, which is later exploited using computational intelligence to classify the quality of superimposed wood particles deposed on a conveyor belt. The method has been tested using synthetic and real images with different noise conditions. The results illustrate the robustness of the approach and its capability to detect significant quality changes in the wood particles.

关键词： Histograms image segmentation Frequency-domain analysis Fourier transforms Belts Robustness

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