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Two-Stage Recognition for Printed Thai and English Characters Using Nearest Neighbor and Support Vector Machine

Two-Stage Recognition for Printed Thai and English Character...

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international IEEE conference on signal-image Technologies and internet-based System

作者： Chayut Wiwatcharakoses Karn Patanukhom Department of Computer Engineering Chiang Mai University Chiang Mai Thailand

In this paper, we introduce a two-stage recognition process for classification of 164 classes of mixing of printed Thai and English characters. Various structural features based on image ratios, image projections, outer boundaries, Pyramid Histogram of Oriented Gradients (PHOG) are extracted from images. In the first stage, Fuzzy C Mean Clustering (FCM) is applied to create prototypes of every character. The class of nearest neighbor prototype is determined and used as the first stage classification output. A hybrid structure of nearest neighbor classifier and Support Vector Machine (SVM) are proposed for the second stage. based on classification results obtained from the first stage, the suitable classifiers can be selected. For SVM classifier, possible class candidates for each prototype are analyzed from confusion matrices of the first stage result. For nearest neighbor classifier, in order to refine the result, accurate search on a limited set of training samples corresponding to the nearest prototypes obtained in the first stage is performed. According to experiments on data set of more than 500,000 character images with various font styles, sizes, and resolutions, we obtain the accuracy of 88.09% in the first stage and the result is improved to 97.06% in the second stage. The experiments also show improvement of the proposed scheme in comparison with conventional schemes.

关键词： Prototypes Support vector machines Training image edge detection Feature extraction Character recognition Training data

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Modeling effects of physical factors on controller area network in cyber-physical systems

Modeling effects of physical factors on controller area netw...

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2013 IEEE international conference on Green Computing and Communications and IEEE internet of Things and IEEE Cyber, Physical and Social Computing, GreenCom-iThings-CPSCom 2013

作者： Shen, Bo Zhou, Xingshe Wang, Ru School of Computer science Northwestern Polytechnical University Xi'an China

ISBN: (纸本)9780769550466

Cyber-physical systems (CPS) are becoming a promising research field to integrate the computing components, the physical processes, and the communication networks. A primary challenge in designing CPS is to understand the effect of physical factors on the communication. In the paper we propose a mathematical model to present the relations between the performance of Controller Area Network (CAN) and some physical factors, such as the temperature, the impedance value and the electromagnetic interference. The first two factors are not considered in previous studies, while the error-arriving models are often used to describe the latter one. The proposed model is based on the probability density function of the voltage generated by noise. Using the model, we can obtain insights into the bit-error rate as a function of these physical factors. Compared to existing error models of CAN, our model is more accurate. Our work provides fundamental insights into the impact of the physical factors on communication. © 2013 IEEE.

关键词： signal interference

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Distributed and Parallel Subarray Beamforming for Near-Field 3D Sonar Imaging 3

Distributed and Parallel Subarray Beamforming for Near-Field...

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3rd international conference on Computer Science and Network technology (ICCSNT)

作者： Han, Yeqiang Fu, Jiabao Zhou, Fan Tian, Xiang Chen, Yaowu Zhejiang Univ Inst Adv Digital Technol & Instrumentat Hangzhou Zhejiang Peoples R China Zhejiang Prov Key Lab Network Multimedia Technol Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781479905614

The computational load is prohibitive in 3D sonar systems for real-time image generation. In the literature, an efficient frequency beamforming method based on the distributed and parallel subarray (DPS) has been introduced for planar arrays working in the far field. This paper extends the DPS beamforming algorithm to process the signals acquired from a scene in the near field. The alogrithm divides the full populated transducer array into two stage distributed subarrays. It performs parallel beamforming on the first-stage subarrays and applies the approximation for time delays in the near-field beam patterns of the second-stage subarray. The computational efficiency is significantly improved as compared with the traditional methods, while achieving the similar resolutions. In addition, a multi-FPGA signal processor is proposed for implementing the underwater 3-D imaging.

关键词： underwater 3D imaging sonar sensor array system sonar signal processing distributed and parallel subarray beamforming

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Motifs in Directed Acyclic Networks

Motifs in Directed Acyclic Networks

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international IEEE conference on signal-image Technologies and internet-based System

作者： C.J. Carstens School of Mathematical and Geospatial Sciences RMIT University Melbourne Australia

ISBN: (纸本)9781479932122

Finding motifs is important for understanding the structure of a network in terms of its building blocks. A network motif is a sub graph that appears significantly more often in a real network than expected in randomised networks. This paper looks at motif detection for a special class of directed networks: directed acyclic networks. Normally, randomised networks are obtained using the switching algorithm. This algorithm preserves the in-degree and out-degree of each node. However, it does not preserve the directed acyclic nature of directed acyclic networks. Karrer and Newman introduced an algorithm that does preserve the directed acyclic property but which may create multiple edges. This paper introduces alternative null-models that maintain the degree sequences, directed acyclic property and do not introduce multiple edges. It is shown that there are explicit formulas for the number of occurrences of each possible 3-node pattern in such random networks. Even though the different random network models result in networks with different properties, the patterns that are keyed as network motifs in three real-world directed acyclic networks do not depend on the choice of null-model. However, when using the switching model as a null-model, sometimes anti-motifs are found that contain directed cycles.

关键词： Switches Feedforward neural networks Physics image edge detection Standards Classification algorithms Educational institutions

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A New Approach for Noise Removal and Video Object Segmentation Using Color based Fuzzy C-Means Technique 2nd

A New Approach for Noise Removal and Video Object Segmentati...

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2nd international conference on Advances in Computing and Informaiton technology (ACITY 2012)

作者： Revathi, R. Hemalatha, M. Karpagam Univ Coimbatore Tamil Nadu India

ISBN: (纸本)9783642315992

Video transmission plays a very important role in traffic applications. Noise can be a big offence in affect-ing encoding efficiency because it can be present throughout an entire application. Noise has the technical definition for various anomalies and unnecessary variations that get built-in into a video signal. Noise re-duction enables better video quality at lower bit rates by making the source look better and decrease the video complication prior to the any process. In this proposed method we adapted the spatial video denois-ing methods, where image noise are reduced and are is applied to each frame individually. Since there is a great deal of removing noise from video content, this paper has been devoted to noise detection and filter-ing methods that aims the removing unwanted noise without affecting the clarity of scenes which contains necessary information and rapid movement. The aim of this work is to produce the exact intensity information of segmentation's neighborhood relationships [I]. In this paper, foreground based segmentation;fuzzy c-means clustering segmentation is compared with the proposed method fuzzy c - means segmentation based on color. This was applied in the video frame to segment various objects in the current frame. The proposed technique is a commanding method for image segmentation and it works for both single and multiple featured data for spatial information. Strong techniques were introduced for finding the number of components in an image. The results done experimentally shows that the proposed segmentation approach generates good quality segmented frames. This paper deals with efficient analysis of noise removal techniques and enhancing the segmentation in video frames.

关键词： image Processing Video Processing Denoising and Filters color segmentation foreground color background color

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2013 2nd international conference on Measurement, Instrumentation and Automation, ICMIA 2013

2013 2nd International Conference on Measurement, Instrument...

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2013 2nd international conference on Measurement, Instrumentation and Automation, ICMIA 2013

ISBN: (纸本)9783037857502

The proceedings contain 498 papers. The special focus in this conference is on Measurement Theory and Its Application, Data Acquisition, signal and Data Processing technology and System, Multimedia signal Processing, image and Video Processing, Intelligence Algorithm, Optimization Algorithm and Artificial Intelligence, Error Theory and Compensation Techniques, Detection and Monitoring. The topics include: 3D measurement method of underground displacement based on hall and MR effect;study on tank capacity table measuring model after the storage tank displacement;rapid measurement of power transformer winding DC resistance;three-dimensional measurement system based on line laser;liquid level measurement system design based on laser displacement sensor;an overview of uncertainty in measurement and its application in ship hydrodynamics;research on the tube system for the pressure measurement;reconfigurable measurement method based on mobile internet;articulated arm length calibration for cantilever coordinate measuring machine;an effective solution to improve GPS position precision;the extension of geodesics;a spatial measurement and statistics method to forecast ore deposits;improvement and application of the maximum bubble pressure tensiometer;dynamic characteristics test of a bearing micro workbench used for fiber measurement;a geo-acoustic model based on empirical formula;load measurement method of the MW class wind turbine;attitude angle measurement method based on the three-dimensional accelerometer;the design of simulating different altitudes ionic mobility measuring device;a twice calibrating method for binocular stereovision system;rotating accuracy measurement system of spindle based on three point method;design of analysis software for measured RCS data;automatic furnace measurement system based on the nuclear scale;soft measurement of heat flux for TEC based dynamic thermal management;the technology of circular parts precise measurement based on binocular ca

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Iterative image fusion using fuzzy logic with applications

引用

2nd international conference on Advances in Computing and Information technology, ACITY 2012

作者： Dammavalam, Srinivasa Rao Maddala, Seetha Krishna Prasad, M.H.M. Department of Information Technology VNRVJIET Hyderabad India Department of CSE GNITS Hyderabad India Department of CSE JNTU College of Engineering Vizianagaram India

ISBN: (纸本)9783642315510

image fusion is the process of reducing uncertainty and minimizing redundancy while extracting all the useful information from the source images. image fusion process is required for different applications like medical imaging, remote sensing, machine vision, biometrics and military applications. In this paper, an iterative fuzzy logic approach utilized to fuse images from different sensors, in order to enhance visualization. The proposed workfurther explores comparison between fuzzy based image fusion and iterative fuzzy fusion technique along with quality evaluation indices for image fusion like image quality index, mutual information measure, root mean square error, peak signal to noise ratio, entropy and correlation coefficient. Experimental results obtained from fusion process prove that the use of the proposed iterative fuzzy fusion can efficiently preserve the spectral information while improving the spatial resolution of the remote sensing images and medical imaging. © 2013 Springer-Verlag.

关键词： Entropy

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A Negative Sample image Selection Method Referring to Semantic Hierarchical Structure for image Annotation

A Negative Sample Image Selection Method Referring to Semant...

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international IEEE conference on signal-image Technologies and internet-based System

作者： Shan-Bin Chan Hayato Yamana Shin'ichi Satoh Waseda University School of Fundamental Science and Engineering Tokyo Japan National Institute of Informatics Tokyo Japan

When SVM is adopted for image annotation, we know that high quality sample images will improve image recognition accuracy. images with the same visual/semantic features are adopted as positive sample images, and images with different visual/semantic features are adopted as negative sample images. But it is labor intensive in high quality sample images selection, especially when collecting by visual features. Most researchers randomly choose positive and negative sample images for classifier training. In many applications, adopting different negative sample image datasets will vary annotation accuracy. In this research, we will discuss the accuracy between different negative sample images dataset collected by semantic features. We adopted image Net as image dataset in this study, and we adopted Word Net for building semantic hierarchical tree. Semantic hierarchical structure tree is adopted to calculate the distance between each node. Then we adopt this distance relationship to prepare positive and negative sample images. We prepare one baseline method and suggest six different negative sample images selection methods for experiment. The binary SVM classifier training and prediction is implemented to compare the accuracy and Mean Reciprocal Rank (MRR) between baseline and each proposed method. Our results show that if we select uniform amount of negative sample images in each distance in the semantic hierarchical tree, we will achieve highest accuracy.

关键词： Semantics Support vector machines Accuracy Feature extraction Training Airplanes Visualization

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Face orientation detection in video stream based on HARR-like feature and LQV classifier for civil video surveillance

Face orientation detection in video stream based on HARR-lik...

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IET international conference on Smart and Sustainable City 2013, ICSSC 2013

作者： Yan, Zhiguo Yang, Fang Wang, Jian Shi, Yongjie Li, Chao Sun, Mingxia Postdoctoral Research Station of Computer Science and Technology Fudan University 200433 Shanghai China Research and Development Centre of Internet of Things Third Research Institute of Ministry of Public Security 201204 Shanghai China Department of Information and Electronic Engineering Shanghai Normal University 200235 Shanghai China

ISBN: (纸本)9781849197076

Most face recognition and tracking techniques employed in surveillance and human-computer interaction (HCI) systems rely on the assumption of a frontal view of the human face. In alternative approaches, knowledge of the orientation angle of the face in captured images can improve the performance of techniques based on non-frontal face views. Face orientation detection plays important role in city surveillance video for the successive specific application, such as the face identification, face recognition and screening face snapshot image for saving the storage volume. In this paper, we propose a kind of method on face orientation by combining Haar-feature and LVQ technique. First, we execute the eye location based on the haar-like feature. Then, we divide the face image into several sub-images and statistical information of the binary sub-image at the eye location. After acquiring the statistical pixel distribution, we exploit the LVQ classifier to execute the classification on face orientation. According to the result, the algorithm we proposed can detect correctly up to 95%. By executing the face orientation classification, we can get the upright fontal face image with the best recognizable and distinctive quality for the further application.

关键词： Face recognition

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An adaptive threshold method based on the local energy of NSCT coefficients for image denoising

An adaptive threshold method based on the local energy of NS...

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international conference on Communication, Electronics, and Automation Engineering, 2012

作者： Liu, Xiyu Yao, Xiaolan Chen, Xin School of Automation Beijing Institute of Technology Beijing China Jinan Diesel Engine Co. Ltd. Jinan China

ISBN: (纸本)9783642316975

In this paper, we propose a new adaptive denoising method based on nonsubsampled Contourlet transform(NSCT). Traditional Wavelet provides only three directional components so that its geometrical property is not well, and Contourlet transform lacks translation invariance, therefore NSCT is developed. The proposed algorithm can adapt different thresholds on different scales and different directions. Further more, we use different thresholds in a directional subband according to local energy of NSCT coefficients to overcome the disadvantages of the unified threshold de-noising method and other fixed thresholds, which cause the image fuzzy distortion because of "over-killed". The experimental results prove that the algorithm outperforms existing schemes in both peak-signal-to-noise-ratio (PSNR) and visual quality. © 2013 Springer-Verlag.

关键词： image denoising

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