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检索条件"任意字段=Conference on Image Processing - Algorithms and Systems VI"

共 15616 条记录，以下是4451-4460 订阅

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DISPARITY MAP ESTIMATION FROM CROSS-MODAL STEREO

DISPARITY MAP ESTIMATION FROM CROSS-MODAL STEREO

引用

IEEE Global conference on Signal and Information processing (GlobalSIP)

作者： Rukkanchanunt, Thapanapong Shibata, Takashi Tanaka, Masayuki Okutomi, Masatoshi Tokyo Inst Technol Tokyo Japan NEC Corp Ltd Tokyo Japan AIST Tokyo Japan

ISBN: (纸本)9781728112954

Mono-modal stereo matching problem has been studied for decades. The introduction of cross-modal stereo systems in industrial scene increases the interest in cross-modal stereo matching. The existing algorithms mostly consider mono-modal setting so they do not translate well in cross-modal setting. Recent development for cross-modal stereo considers small local matching and focus mainly on joint enhancement. Therefore, we propose a guided filter-based stereo matching algorithm. It works by integrating guided filter equation in a basic cost function for cost volume generation. The cost volume can be further improved via smoothness constraints and confidence filtering. We show that the proposed algorithm is able to estimate disparity correctly within acceptable interval in many important regions and outperforms many existing algorithms. We believe that the proposed algorithm will become the new benchmark for cross-modal stereo matching problem.

关键词： disparity map stereo systems cross-modality thermal image visible image

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Non-Planar Inside-Out Dense Light-Field Dataset and Reconstruction Pipeline

Non-Planar Inside-Out Dense Light-Field Dataset and Reconstr...

引用

IEEE International conference on image processing

作者： Faezeh Sadat Zakeri Ahmed Durmush Matthias Ziegler Michel Bätz Joachim Keinert Fraunhofer IIS Erlangen Germany Tampere University Tampere Finland

Light-field imaging provides full spatio-angular information of the real world by capturing the light rays in various directions. This allows image processing algorithms to result in immersive user experiences such as VR. To evaluate, and develop reconstruction algorithms, a precise and dense light-field dataset of the real world that can be used as ground truth is desirable. In this paper, a non-planar capture is done and a view rendering pipeline is implemented. The acquired dataset includes two scenes that are captured by an accurate industrial robot with an attached color camera such that the camera is looking outward. The arm moves on a cylindrical path for a field of view of 125 degrees with angular step size of 0.01 degrees. Both scenes and their corresponding geometric calibration parameters will be available with the publication of the paper. The images are pre-processed in different steps. The disparity between two adjacent views with resolution of 5168×3448 is less than 1.6 pixels; the parallax between the foreground and the background objects is less than 0.6 pixels. Furthermore, the pre-processed data is used for a view rendering experiment to demonstrate an exemplary use case. In addition, the rendered results are evaluated visually and objectively.

关键词： Cameras Rendering (computer graphics) Pipelines image color analysis Robot vision systems Calibration

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Hyperspectral image classification based on pre-post combination process

Hyperspectral image classification based on pre-post combina...

引用

International conference on systems and Informatics (ICSAI)

作者： Kaiqing Luo Yang Qin Dan Yin Hua Xiao School of Physics and Telecommunication Engineering South China Normal University Guangzhou Guangdong China

ISBN: (数字)9781728152561

ISBN: (纸本)9781728152578

Aiming at the problem of poor classification accuracy of traditional machine learning algorithms based on spectral information analysis, this paper proposes a hyperspectral image classification method based on pre-processing before classification and processing optimization combination after classification. Firstly, the original samples are subjected to Gaussian filter and Linear discriminant analysis for reducing noise and dimensions. Then, the data is initially classified by traditional machine learning algorithms such as k-nearest neighbor(KNN), Support Vector Machine (SVM), sparse representation-based classifier (SRC)or multiple logistic regression (MLR). Combining local pixel spatial information to determine the confidence of the prediction labels. Finally, the initial prediction label is corrected by a continuous multi-layer neighborhood optimization layers to obtain a final classification label. Comparative experiments were performed on multiple hyperspectral remote sensing databases such as Indian Pines. The experimental results show that the proposed method has obvious performance improvement in classification accuracy and time efficiency, which has a certain degree of robustness in the process of combining with different classifiers.

关键词： Hyperspectral imaging Classification algorithms Optimization Databases Feature extraction image classification

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SET: Stereo Evaluation Toolbox for Combined Performance Assessment of Camera systems, 3D Reconstruction and visual SLAM

SET: Stereo Evaluation Toolbox for Combined Performance Asse...

引用

IEEE International conference on Information Communication and Signal processing (ICICSP)

作者： Nina Felicitas Heide Alexander Albrecht Michael Heizmann Systems for Measurement Control and Diagnosis Fraunhofer IOSB Karlsruhe Germany Institute of Industrial Information Technology Karlsruhe Institute of Technology Karlsruhe Germany

Evaluating stereo reconstruction algorithms regardless of camera system and application environment is not sufficient to rate the overall performance of a stereo system. To overcome this the Stereo Evaluation Toolbox (SET) proposes a well-founded selection and comparison approach for stereo systems. We aim at providing one performance score evaluating the generated stereo point cloud, complementary to common benchmarks which solely evaluate stereo algorithms on provided image sets. Using images captured in the desired application environment SET measures and compares performance as interaction of modular camera-algorithm combinations inside a local application scenario. Furthermore an evaluation approach for camera-based visual simultaneous localization and mapping (SLAM) systems is presented for further analysis. We apply SET on the evaluation of different camera systems in 3D reconstruction of indoor and outdoor environments as well as on visual SLAM for person indoor navigation.

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Efficient image Secret Sharing Using Parallel processing for Row-Wise Encoding and Decoding 3rd

Efficient Image Secret Sharing Using Parallel Processing for...

引用

3rd International conference on Intelligent Computing and Applications (ICICA)

作者： Patil, Sonali D. Pimpri Chinchwad Coll Engn Dept Comp Engn Pune 411044 Maharashtra India

ISBN: (纸本)9789811055201;9789811055195

Secret sharing plays a vital role in secure transmission of secret information in the form of images. Majority of the secret sharing algorithms are build using Lagrange's Interpolation due its information theoretic secure property. These image-sharing algorithms use pixel values of images for construction of shares and uses share's pixel values for reconstruction of a secret. The larger the size of an image the pixel values are more. The problem with such image secret sharing algorithm is its large computational complexity while implementing it in real-time application. A concurrent approach is proposed here for row-wise encoding and decoding. The concurrent approach helps to expedite the construction and reconstruction process. The proposed approach is implemented using UNIX-based Quadra Core system. The algorithm improves the time complexity of the construction and reconstruction process. The step-up of the concurrent algorithm is relatively even.

关键词： Secret sharing Parallel algorithm Cryptography image processing

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Survey of image processing Techniques in Medical image Analysis: Challenges and Methodologies 8th

Survey of Image Processing Techniques in Medical Image Analy...

引用

8th International conference on Soft Computing and Pattern Recognition (SoCPaR) / 8th International conference on Computational Aspects of Social Networks (CASoN)

作者： Chinmayi, P. Agilandeeswari, L. Prabukumar, M. VIT Univ Sch Informat Technol & Engn Vellore Tamil Nadu India

ISBN: (纸本)9783319606187;9783319606170

Due to the tremendous increase in the usage of computer technologies, image-processing techniques have become one among the most important and rapidly used one in a wide variety of applications, especially in medical imaging. The basic idea of the medical image analysis is to improve the imaging content. A typical medical imaging system is composed of five main processing steps namely, image acquisition, enhancement, segmentation, feature extraction/selection and classification. In this paper, we have done a study on the current state - of - art techniques that have been used in various stages of medical image analysis. The methodologies used and technical issues in each stage have been discussed. In addition, this paper also addresses the challenges faced by researchers during the implementation and outline of the pros and cons of the existing algorithms.

关键词： Medical image analysis Enhancement Segmentation Feature extraction Classification

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Simultaneous Localisation And Mobilisation Using image processing

Simultaneous Localisation And Mobilisation Using Image Proce...

引用

Intelligent Computing and Control systems (ICCS), International conference on

作者： Sahaya Sakila V. Abishek Narayanan Adithya Sai Selva Sabbarish Khanna S. SRM Institute of Science and Technology Chennai SRM Institute of Science and Technology Chennai India

ISBN: (数字)9781538681138

ISBN: (纸本)9781538681145

SLAM(Simultaneous Localisation And Mobilisation) is a problem in robotics that revolves around the idea of a robot which can map a location by moving around in a sequential manner. Robot has to move and as well as recognize the path its traversing through by stitching the images into a map. Most models that have been created till now only focuses on small scale indoor applications and do not have a scope for real time usage outside an experimental area. Our project focuses on a large scale approach on the problem that deals with ambiguity of real life scenarios and also additional features like pinpointing its location. Neural networks is used for image processing and mapping and various robotics algorithms are used for the mobilisation of the robot.

关键词： Robots Global Positioning System Roads Neural networks Probabilistic logic Heuristic algorithms conferences

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Histopathological image Classification: Defying Deep Architectures on Complex Data 2nd

Histopathological Image Classification: Defying Deep Archite...

引用

2nd International conference on Recent Trends in image processing and Pattern Recognition, RTIP2R 2018

作者： Tripathi, Suvidha Singh, Satish Indian Institute of Information Technology Allahabad Devghat Jhalwa AllahabadU. P.211015 India

ISBN: (纸本)9789811391835

Automatic analysis of medical images is a challenging research which requires both the skill of a pathologist and computer vision knowledge to develop efficient systems. In this work, we have taken up the task of classifying different types of cell nuclei in histopathological Colon Cancer images. We aim to show the relevance and effect of a complex histopathological dataset on the performance of current deep learning architectures. We have experimented with pre-trained (on imageNet) AlexNet, VGG16, and VGG19 architectures and applied transfer learning approach to train these architectures. On the basis of the results obtained on the Histopathological image dataset, while using fine tuned AlexNet, VGG16, and VGG19 architectures;the suitability of using pure architectures is somehow questionable and these state of the art algorithms straightaway cannot be used for the sophisticated classification of very complex cancer tissue dataset. Comparative evaluation of the above state of the art methods have been done and the possibility of devising hybrid deep architectures is investigated thereof. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Classification (of information)

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Anomaly Detection of Software System Logs based on Natural Language processing

Anomaly Detection of Software System Logs based on Natural L...

引用

International conference on image and video processing, and Artificial Intelligence (IVPAI)

作者： Wang, Mengying Xu, Lele Guo, Lili Chinese Acad Sci Technol & Engn Ctr Space Utilizat Key Lab Space Utilizat Beijing 100094 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

ISBN: (数字)9781510623118

ISBN: (纸本)9781510623118

System logs record the daily status of operating systems, application software, firewalls, etc. Analyzing system logs can help to prevent and eliminate information security events in real time. In this paper, we propose to analyze the system logs for anomalous event detection based on natural language processing. First, we use doc2vec of natural language processing algorithm to construct sentence vectors, then apply several state-of-the-art classification algorithms on the sentence vectors for anomaly detection. The system logs generated by the Thunderbird supercomputer are adopted here to verify the proposed method. The results show that doc2vec combined with machine learning classification algorithms could not only effectively extract the semantic information of the logs, but also perform excellent anomaly detection.

关键词： anomaly detection natural language processing machine learning classification algorithms

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Digital Signal processing Based On Spline Functions

Digital Signal Processing Based On Spline Functions

引用

International conference on Information Science and Communications Technologies (ICISCT)

作者： Avaz Mirzaev Sirojiddin Khalilov Information technologies dept Tashkent university of information technologies named after Muhammad al-Khwarizmi (TUIT) Tashkent Uzbekistan

ISBN: (数字)9781728125640

ISBN: (纸本)9781728125657

The development of the modern world's information and communication technologies and their implementation in various industries are important, are essential to the creation of parallel algorithms for solving problems of the recovery and digital signal processing, on the basis of the treatment processes a multi-core architecture and the search for optimal solutions. The current stages of development of the structure of machines, complexes and systems installed at facilities that are part of the structure of devices specialized for conducting scientific research or located on rolling stock are characterized by on-line analysis of complex processes and fields and increased demands on the speed of processing large amounts of data in real time. Particular attention is paid to the development of methods for solving problems of image and signal processing by using modern methods, algorithms and structural tools, architecture of computing and software. In that work the result of the study of methods of approximation of functions and functional dependencies obtained in the course of experiments for the selected class of signals improved method of spline functions on the basis of analytical analysis, parallel algorithms for digital signal processing have been developed, efficient algorithms have been developed for digital processing of vibrio signals in multi-core processors based on cubic and bi cubic basis splines.

关键词： Splines (mathematics) Computer architecture Interpolation Signal processing algorithms Digital signal processing Mathematical model Parallel algorithms

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