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Automatic classification of metallic targets using pattern recognition of GPR reflection: a study in the IAG-USP Test Site, Sao Paulo (Brazil)

Automatic classification of metallic targets using pattern r...

引用

Proceedings of the international conference on Ground Penetrating Radar, GPR

作者： Vinicius R.N. dos Santos Jorge L. Porsani Nina S. T. Hirata Departamento de Geofísica Universidade de Sao Paulo Sao Paulo Brazil Departamento de Ciencia da Computacao Universidade de Sao Paulo Sao Paulo Brazil

ISBN: (纸本)9781424446049;9781424446056

In this work, a methodology to automatically classify of metal targets using pattern recognition techniques on GPR reflection data is presented. The methodology consists of designing a multilayer perceptron (MLP) classifier based on features extracted from the targets in the subsoil, and then using it to classify hyperbolas diffraction indicating their position and depth. The classification of reflections allows a high resolution reconstruction of the subsurface with reduced computing time. The system was developed in MATLAB and applied to GPR data obtained at IAG-USP test site, located in the city of Sao Paulo, Brazil, where metallic drums were studied under controlled field conditions. This site contains different targets of variable sizes buried under different depths and it served as a model for the computational experiment. The results indicate that the automatic classification of the metallic targets in the subsoil is efficient, contributing for the reduction of the ambiguities in the geophysical data interpretation, besides having application on the subsoil mapping of utilities.

关键词： pattern recognition Ground penetrating radar Reflection Automatic testing Geophysics computing Design methodology Multilayer perceptrons Feature extraction Data mining Diffraction

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An Efficient Algorithm of Hot Events Detection in Text Streams

An Efficient Algorithm of Hot Events Detection in Text Strea...

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international conference on Cyber-Enabled Distributed computing and Knowledge Discovery, CyberC

作者： Junliang Bai Jun Guo Guang Chen Weiran Xu Gang Du Pattern Recognition & Intelligent System Lab Beijing University of Posts and Telecommunications China

Hot events detection in text streams has drawn increasing attention in recent sequential data mining works. Different from traditional TDT task which find all the real events' cluster, hot events detection only identify hot events concerned by public. This paper proposes a novel approach to identify those events based on burst terms, terms co-occurrence and generative probabilistic model. Experiments with huge text stream sets crawled from WWW suggest that our algorithm can work on-line and identify hot events effectively and efficiently.

关键词： Event detection Algorithm design and analysis Earthquakes Web sites Clustering algorithms Computational modeling Helium

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Efficient Path Planning Method Based on Genetic Algorithm Combining Path Network

Efficient Path Planning Method Based on Genetic Algorithm Co...

引用

international conference on Genetic and Evolutionary computing (ICGEC)

作者： Shidong Li Mingyue Ding Chao Cai Lei Jiang Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan China Hubei University for Nationalities Enshi Hubei China

Fast algorithm for path planning is helpful for artificial intelligence. Genetic Algorithm (GA) is a typical evolution method, used widely in path planning. A new GA based on path network is proposed in this paper. Efficient chromosome encoding strategy provided guarantees, and each chromosome represents a feasible path, avoiding the searching circulation. Variation happens at certain positions, making the algorithm assemble quickly. Experimental result shows that the GA combining with path network can plan path quickly. By means of path cells, it works efficiently to produce multi path simultaneously.

关键词： Biological cells Path planning Gallium Encoding Planning Genetic algorithms Pixel

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High-Capacity Multi-secret Sharing by Random Grid

High-Capacity Multi-secret Sharing by Random Grid

引用

international conference on Broadband, Wireless computing, Communication and Applications (BWCCA)

作者： Tzung-Her Chen Yao-Sheng Lee Ci-Lin Li Department of Computer Science & Information Engineering National Chiayi University Chiayi Taiwan

It's well-known that visual secret sharing aims at encrypting a secret image into numerous meaningless sharing images by either designing a well-designed codebook or generating random bit sequence, and reconstructing the secret by superimposing them without any computation involved. However, the traditional visual secret sharing schemes only deal with one secret at a time. In this paper, the authors proposed a multi-secret sharing scheme by random grids such that the following advantages are obtained: 1) removing the restriction of limited secret images encrypted into two cipher-grids 2) removing the problem of suffering pixel expansion, and 3) without the need of designing tailor-made codebook.

关键词： Visualization Pixel Encryption Stacking Watermarking pattern recognition

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An Algorithm of Sphere-structure Support Vector Machine Multi-classification recognition on the Basis of Weighted Relative Distances

An Algorithm of Sphere-structure Support Vector Machine Mult...

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2010 international conference on Life System Modeling and Simulation & 2010 international conference on Intelligent computing for Sustainable Energy and Environment

作者： Shiwei Yun,Yunxing Shu, Bo Ge Luoyang Institute of Science and Technology Henan, Luoyan,471003, China

Theories on sphere-structure support vector machine (SVM) and multi-classification recognition algorithms were studied in the first place, and on this basis, in view of the issue of the difference in the hypersphere radiuses resulted from the difference in the quantity of the training samples and the discrepancy in their distributions, the concepts of relative distance and weight were introduced, and subsequently a new algorithm of sphere-structure SVM multi-classification recognition was proposed on the basis of weighted relative distances. Accordingly, the data from the UCI database were used to conduct simulation experiments, and the results verified the validity of the algorithm propose

关键词： pattern recognition sphere-structure SVM relative distance weighting

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Graph-Based Text Segmentation Using a Selected Channel Image

Graph-Based Text Segmentation Using a Selected Channel Image

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Proceedings of the Digital Image computing: Technqiues and Applications (DICTA)

作者： Chao Zeng Wenjing Jia Xiangjian He Jie Yang INEXT FEIT University of Technology Sydney Australia Institute of Image Processing and Pattern Recognition Shanghai Jiaotong University Shanghai China

This paper proposes a graph-based method for segmentation of a text image using a selected colour-channel image. The text colour information usually presents a two polarity trend. According to the observation that the histogram distributions of the respective colour channel images are usually different from each other, we select the colour channel image with the histogram having the biggest distance between the two main peaks, which represents the main foreground colour strength and background colour strength respectively. The peak distance is estimated by the mean-shift procedure performed on each individual channel image. Then, a graph model is constructed on a selected channel image to segment the text image into foreground and background. The proposed method is tested on a public database, and its effectiveness is demonstrated by the experimental results.

关键词： Pixel Image color analysis Image segmentation Histograms Lighting Text recognition Kernel

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A Genetic type-2 fuzzy logic system for pattern recognition in computer aided detection systems

A Genetic type-2 fuzzy logic system for pattern recognition ...

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IEEE international conference on Fuzzy Systems (FUZZ-IEEE)

作者： Rahil Hosseini Jamshid Dehmeshki Sarah Barman Mahdi Mazinani Salah Qanadli Department of Computing Information Systems and Mathematics Kingston University London UK Departments of Radiology and Cardiology Lausanne Hospital Switzerland

A computer aided detection (CAD) system suffers from vagueness and imprecision in both medical science and image processing techniques. These uncertainty issues in the classification components of a CAD system directly influence the accuracy. This paper takes advantage of type-2 fuzzy sets as three-dimensional fuzzy sets with high potential for managing uncertainty issues in vague environments. In this paper, an automatic optimized approach for generating and tuning type-2 Gaussian membership function (MF) parameters and their footprint of uncertainty is proposed. In this approach, two interval type-2 fuzzy logic system (IT2FLS) methods based on the Mamdani rules model are presented for tackling the uncertainty issues in classification problems in pattern recognition. Furthermore, the Genetic algorithm is employed for tuning of the MFs parameters and footprint of uncertainty. In order to assess the performance, the designed IT2FLSs are applied on a lung CAD application for classification of nodules. The ROC accuracy and mean absolute error (MAE) are considered as the performance indicators. The results reveal that the Genetic IT2FLS classifier outperforms the equivalent type-1 FLS and is capable of capturing more uncertainties.

关键词： Uncertainty Fuzzy sets Fuzzy logic Genetics Design automation pattern recognition Classification algorithms

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A new wavelet-median-moment based method for multi-oriented video text detection 10

A new wavelet-median-moment based method for multi-oriented ...

引用

2010 IAPR Workshop on Document Analysis Systems, DAS 2010

作者： Shivakumara, Palaiahnakote Dutta, Anjan Tan, Chew Lim Pal, Umapada Department of Computer Science School of Computing National University of Singapore Singapore Singapore Computer Vision and Pattern Recognition Unit Indian Statistical Institute Kolkata India

ISBN: (纸本)9781605587738

In this paper, we present a new method based on wavelet-median-moments and a novel idea of angle projection for detecting multi-oriented text in video. The proposed method uses wavelet decomposition first to obtain three high frequency sub-bands (LH, HL and HH) and then median moments are computed on the average sub-bands of the three high frequency sub-bands to brighten the text pixels. K-means clustering (K=2) is used for obtaining text pixels from the wavelet-median-moments features (WMMF). Text candidates are obtained by mapping the output of K-means on Sobel edge map of the original input frame. To deal with multi-oriented text, we introduce a new idea of Angle Projection (AP) based on boundary growing and nearest neighbor concepts from the text candidates instead of conventional projection profiles. The proposed method is experimented on horizontal text data, non-horizontal text data, temporal data, non-text data and camera based images (scene text data of ICDAR 2003 competition) to show that the proposed method is superior to existing methods. © Copyright 2010 ACM.

关键词： Pixels

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Model-based esophagus segmentation from CT scans using a spatial probability map

引用

13th international conference on Medical Image computing and Computer-Assisted Intervention, MICCAI 2010

作者： Feulner, Johannes Kevin Zhou, S. Huber, Martin Cavallaro, Alexander Hornegger, Joachim Comaniciu, Dorin Pattern Recognition Lab. University of Erlangen-Nuremberg Germany Siemens Corporate Research Princeton NJ United States Siemens Corporate Technology Erlangen Germany Radiology Institute University Hospital Erlangen Germany

ISBN: (纸本)3642157041

Automatic segmentation of the esophagus from CT data is a challenging problem. Its wall consists of muscle tissue, which has low contrast in CT. Sometimes it is filled with air or remains of orally given contrast agent. While air holes are a clear hint to a human when searching for the esophagus, we found that they are rather distracting to discriminative models of the appearance because of their similarity to the trachea and to lung tissue. However, air inside the respiratory organs can be segmented easily. In this paper, we propose to combine a model based segmentation algorithm of the esophagus with a spatial probability map generated from detected air. Threefold cross-validation on 144 datasets showed that this probability map, combined with a technique that puts more focus on hard cases, increases accuracy by 22%. In contrast to prior work, our method is not only automatic on a manually selected region of interest, but on a whole thoracic CT scan, while our mean segmentation error of 1.80mm is even better. © 2010 Springer-Verlag.

关键词： Computerized tomography

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Study on the Method of Image Restoration in the Environment of Dust

Study on the Method of Image Restoration in the Environment ...

引用

international conference on Wireless Communications, Networking and Mobile computing (WiCom)

作者： Yuanyu Wang Yuanzong Li Tianxu Zhang Department of Computer Fundamental Education Taiyuan University Of Technology Taiyuan China College of Mechanical Engineering Taiyuan University Of Technology Taiyuan China Institute of Pattern Recognition and A.I State Key Laboratory of Image Processing and Intelligent Control HuaZhong University of Science and Technology Wuhan China

In order to solve the problem of image degradation caused by dust environments, an image degradation model considering multiple scattering factors caused by dust was first established using the first-order multiple scattering method. Then, a dark channel prior principle was applied to present an image restoration algorithm based on the image degradation model. Finally, GA optimization algorithm was applied to optimize the atmospheric light and the exposure parameters. This optimization algorithm was established according to the criterion of the image evaluation based on kirsch operator with automatic threshold. By using the method an optimistic result of image restoration was obtained. The experimental results have shown that the method not only enhanced luminance and contrast, but also discovered more detail edges information. The method provided a foundation for target recognition in the dust environments.

关键词： Image edge detection Image restoration Scattering Degradation Gallium Atmospheric modeling Genetic algorithms

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