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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Lv, Qi Dou, Yong Niu, Xin Xu, Jiaqing Xu, Jinbo Natl Univ Def Technol Sch Comp Sci & Technol Parallel & Distributed Proc Lab Changsha 410073 Hunan Peoples R China Natl Univ Def Technol Sch Comp Changsha 410073 Hunan Peoples R China

ISBN: (纸本)9781467372206

The hyperspectral remote sensing is one of the frontier techniques in the remote sensing research fields. Applying the sparse coding model to the hyperspectral remote sensing image processing is a hot topic in hyperspectral information processing. To improve the accuracy of hyperspectral image classification, we propose a classification method based on the spatial-spectral joint contextual sparse coding. Firstly, a dictionary is obtained by training using samples selected from the ground-truth reference data. Then, the sparse coefficients of each pixel are calculated based on the learned dictionary. Afterward, the sparse coefficients are input to the classifier and the final classification result is obtained. The visible and near-infrared hyperspectral remote sensing image collected by Tiangong-1 in Chaoyang District of Beijing is used to evaluate the performance of the proposed approach. Experimental results show that the proposed method yields the best classification performance with the overall accuracy of 95.74% and the Kappa coefficient of 0.9476 in comparison with other classification methods.

关键词： Hyperspectral image Remote sensing Sparse coding

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Location-Based parallel Tag Completion for Geo-tagged Social image Retrieval 15

Location-Based Parallel Tag Completion for Geo-tagged Social...

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5th ACM International Conference on Multimedia Retrieval (ICMR)

作者： Zhang, Jiaming Wang, Shuhui Huang, Qingming Chinese Acad Sci Inst Comp Technol Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing 100049 Peoples R China

ISBN: (纸本)9781450332743

Benefit from tremendous growth of user-generated content, social annotated tags get higher importance in organization and retrieval of large scale image database on Online Sharing Websites (OSW). To obtain high-quality tags from existing community contributed tags with missing information and noise, tag-based annotation or recommendation methods have been proposed for performance promotion of tag prediction. While images from OSW contain rich social attributes, existing studies only utilize the relations between visual content and tags to construct global information completion models. In this paper, beyond the image-tag relation, we take full advantage of the ubiquitous GPS locations and image-user relationship, to enhance the accuracy of tag prediction and improve the computational efficiency. For GPS locations, we define the popular geo-locations where people tend to take more images as Points of Interests (POI), which are discovered by mean shift approach. For image user relationship, we integrate a localized prior constraint, expecting the completed tag sub-matrix in each POI to maintain consistency with users' tagging behaviors. Based on these two key issues, we propose a unified tag matrix completion framework which learns the image-tag relation within each POI. To solve the proposed model, an efficient proximal sub-gradient descent algorithm is designed. The model optimization can be easily parallelized and distributed to learn the tag sub-matrix for each POI. Extensive experimental results reveal that the learned tag sub-matrix of each POI reflects the major trend of users' tagging results with respect to different POIs and users, and the parallel learning process provides strong support for processing large scale online image database.

关键词： tag matrix completion geo-location information social image retrieval

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International Conference on image processing and Communications, IP and C 2015

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International Conference on image processing and Communications, IPandC 2015

ISBN: (纸本)9783319238135

The proceedings contain 34 papers. The special focus in this conference is on image processing and Communications. The topics include: Classifier selection uses decision profiles in binary classification task;2DHMM-based face recognition method;corner detection based on directional gradients;sensor fusion enhancement for mobile positioning systems;thermal face recognition;feature reduction using similarity measure in object detector learning with haar-like features;assessment of the brain coverage ratio in the postoperative craniosynostosis based on 3D CT scans;combined imaging system for taking facial portraits in visible and thermal spectra;the PUT surveillance database;automatic analysis of vehicle trajectory applied to visual surveillance;algorithmically optimized AVC video encoder with parallel processing of data;neural video compression based on SURF scene change detection algorithm;cell detection in corneal endothelial images using directional filters;the method of probabilistic nodes combination in 2D information retrieval, pattern recognition and biometric modeling;3-D reconstruction of real objects using an android device;methods of natural image preprocessing supporting the automatic text recognition using the OCR algorithms;fast machine vision line detection for mobile robot navigation in dark environments;adjustment of viterbi algorithm for line following robots;studentized range for spatio-temporal track-before-detect algorithm;real-time US image enhancement by forward-backward diffusion using GPU;face-based distributed visitor identification system;color space optimization for lacunarity method in analysis of papanicolaou smears and toward texture-based 3D level set image segmentation.

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COMPARISON OF LASER SCANNING AND PHOTOGRAMMETRY AND THEIR USE FOR DIGITAL RECORDING OF CULTURAL MONUMENT CASE STUDY: BYZANTINE LAND WALLS-ISTANBUL 25

COMPARISON OF LASER SCANNING AND PHOTOGRAMMETRY AND THEIR US...

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25th International CIPA Symposium 2015

作者： Bayram, B. Nemli, G. Ozkan, T. Oflaz, O. E. Kankotan, B. Cetin, I. YTU Fac Civil Engn Dept Geomat Engn Div Photogrammetry Davutpasa Campus TR-34210 Istanbul Turkey Survey & Project Dept Fatih Municipal TR-34080 Istanbul Turkey Yildiz Tech Univ Piksel Teknol Co TR-34210 Istanbul Turkey Galata Restorat Architecture TR-34083 Istanbul Turkey

3D modeling of cultural monuments is very crucial issue for preparing restoration projects. However, it has challenges such as data acquisition, preparation and processing. 3D modeling of objects can be time consuming and may include some difficulties due to the complexity of the structures. 3D terrestrial laser (TLS) scanning technique is one of the reliable and advantageous methods for 3D reconstruction of monuments. This technique is commonly acknowledged due to its accuracy, speed and flexibility. But the suitability and capability of this technique depends on proper usage, and good survey planning. Magnificent developments in high-resolution digital sensor technologies leaded to manufacturing of new camera systems. parallel to these innovations, development of computer systems and image processing techniques made enable to obtain multiple image-based 3D object models. In the presented study, TLS method has been compared to conventional photogrammetric and image-based dense matching methods. Automatic dense point creation has been realized by our developed algorithm and PIXEL-PHOTO software which generates 3D point clouds from stereo images. The reliability and encountered problems during point cloud measurement process have been discussed. The study area has been chosen as historical Byzantine Land Walls of Istanbul, which constitute a remarkable area defining the ancient city's historical peninsula.

关键词： Cultural Heritage Terrestrial Laser Scanning image matching Photogrammetry 3D Modeling

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基于FPGA的图像处理系统

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华中科技大学学报（自然科学版） 2015年第2期43卷 119-123页

作者：杨帆张皓马新文姜勇武汉工程大学电气信息学院湖北武汉430073 武汉工程大学湖北省智能机器人重点实验室湖北武汉430073

针对目前采用通用计算机、多CPU并行、DSP等方法实现实时图像处理的不足,研究了一种基于FPGA的图像处理系统,由图像采集和图像处理基本算法两部分组成.图像采集选用OV7670图像传感器,其内部集成了传感器及图像处理单元,可以直接输出数... 详细信息

针对目前采用通用计算机、多CPU并行、DSP等方法实现实时图像处理的不足,研究了一种基于FPGA的图像处理系统,由图像采集和图像处理基本算法两部分组成.图像采集选用OV7670图像传感器,其内部集成了传感器及图像处理单元,可以直接输出数字信号给FPGA.图像处理选用Altera公司的Cyclone ii系列的FPGA芯片,在芯片上完成了图像采集的控制,模拟了I2 C总线协议,通过设计FPGA的内部逻辑实现了图像灰度化、中值滤波、边缘检测等图像处理基本算法,使处理速度远远快于软件方法.仿真结果显示:该系统实现了实时图像的快速采集和处理,最高能达到30帧/s,并且分辨率为640×480.

关键词：图像处理图像采集边缘检测中值滤波算法

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基于分布式计算的遥感图像水体识别研究

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计算机应用与软件 2016年第6期33卷 138-140,145页

作者：杨柳田生伟新疆大学软件学院新疆乌鲁木齐830046

为了提高遥感数据的处理速度,解决遥感信息提取中的数据密集与计算密集问题,将并行计算的思想引入到遥感图像的处理与信息提取中,构建基于Landsat ETM+影像的分布式遥感图像水体提取模型。以渭干河流域为研究区,利用单波段阈值法、多波... 详细信息

为了提高遥感数据的处理速度,解决遥感信息提取中的数据密集与计算密集问题,将并行计算的思想引入到遥感图像的处理与信息提取中,构建基于Landsat ETM+影像的分布式遥感图像水体提取模型。以渭干河流域为研究区,利用单波段阈值法、多波段谱间关系法、水体指数法等方法进行水体信息自动提取的实验。实验结果表明,该模型具有较高的识别精度,能够快速识别水体,并具有稳定的可扩展性和伸缩性。

关键词：大数据遥感水体识别并行计算

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A review on parallel medical image processing on GPU

A review on parallel medical image processing on GPU

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International Conference on Software Engineering and Computer Systems (ICSECS)

作者： Hui Liang Khor Siau-Chuin Liew Jasni Mohd Zain Faculty of Computer Systems and Software Engineering University Malaysia Pahang Lebuhraya Tun Razak Malaysia

An efficient implementation are necessary, as most medical imaging methods are computational expensive, and the amount of medical imaging data is growing. Graphic processing units (GPUs) can solve large data parallel problems at a higher speed than the traditional CPU, while being more affordable and energy efficient than distributed systems. This review investigates the use of GPUs to accelerate medical imaging methods. A set of criteria for efficient use of GPUs are defined. The review concludes that most medical image processing methods may benefit from GPU processing due to the methods' data parallel structure and high thread count. However, factors such as synchronization, branch divergence and memory usage can limit the speedup.

关键词： Graphics processing units Instruction sets Synchronization Biomedical imaging parallel processing Algorithm design and analysis Biomedical image processing

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ACM TRANSACTIONS ON MULTIMEDIA COMPUTING COMMUNICATIONS AND APPLICATIONS 2015年第4期11卷 51-51页

作者： Antaris, Stefanos Rafailidis, Dimitrios Aristotle Univ Thessaloniki Sch Informat Thessaloniki 54124 Greece

In recognition that inmodern applications billions of images are stored into distributed databases in different logical or physical locations, we propose a similarity search strategy over the cloud based on the dimensions value cardinalities of image descriptors. Our strategy has low preprocessing requirements by dividing the computational cost of the preprocessing steps into several nodes over the cloud and locating the descriptors with similar dimensions value cardinalities logically close. New images are inserted into the distributed databases over the cloud efficiently, by supporting dynamical update in real-time. The proposed insertion algorithm has low computational complexity, depending exclusively on the dimensionality of descriptors and a small subset of descriptors with similar dimensions value cardinalities. Finally, an efficient query processing algorithm is proposed, where the dimensions of image descriptors are prioritized in the searching strategy, assuming that dimensions of high value cardinalities have more discriminative power than the dimensions of low ones. The computation effort of the query processing algorithm is divided into several nodes over the cloud infrastructure. In our experiments with seven publicly available datasets of image descriptors, we show that the proposed similarity search strategy outperforms competitive methods of single node, parallel and cloud-based architectures, in terms of preprocessing cost, search time and accuracy.

关键词： Algorithms Measurement Experimentation Content-based image retrieval large-scale similarity search distributed databases multimedia cloud computing

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Test oracles based on metamorphic relations for image processing applications

Test oracles based on metamorphic relations for image proces...

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ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and parallel/distributed Computing (SNPD)

作者： Tahir Jameel Mengxiang Lin Liu Chao State key Lab of Software Development Environment Beihang University Beijing China

Testing of image processing applications is a challenging job especially, when evaluating the correctness of output image. Generally, output images are evaluated manually by visual inspection carried out by an expert tester, which is the main hindrance in automation of testing process. Recently, statistical and metamorphic testing approaches are presented to automate output evaluation of image processing applications. The statistical method is dependent on availability of statistical distribution of output images, whereas metamorphic testing require more research efforts to make it widely used in practice. Metamorphic testing is a well-known technique to alleviate the test oracle problem and eliminates the required manual efforts by using relations of input and output images. Follow-up test cases are generated based on these relations and their expected output is evaluated. This paper addresses test oracle problem for image processing applications and demonstrates how properties of implementation under test can be adopted as metamorphic relations. We have studied general and specific metamorphic relations of morphological image operations such as dilation and erosion. Selection of metamorphic relations and their effectiveness by mutation analysis is demonstrated. The results show that metamorphic testing is useful for evaluation of output images in the absence of a perfect test oracle.

关键词： Testing image processing Software algorithms Standards Smoothing methods Noise Software

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Artificial Intelligence and Soft Computing: 14th International Conference, ICAISC 2015, Zakopane, Poland, June 14-28, 2015, Proceedings, Part ii 1

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丛书名： Lecture Notes in Computer Science 9119

2015年

作者： Leszek Rutkowski, Marcin Korytkowski, Rafal Scherer, Ryszard Tadeusiewicz, Lotfi A. Zadeh, Jacek M. Zurada (eds.)

ISBN: (数字)9783319193687;9783319193694

ISBN: (纸本)9783319193687;9783319193694

The two-volume set LNAI 9119 and LNAI 9120 constitutes the refereed proceedings of the 14th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2015, held in Zakopane, Poland in June 2015. The 142 revised full papers presented in the volumes, were carefully reviewed and selected from 322 submissions. These proceedings present both traditional artificial intelligence methods and soft computing techniques. The goal is to bring together scientists representing both areas of research. The first volume covers topics as follows neural networks and their applications, fuzzy systems and their applications, evolutionary algorithms and their applications, classification and estimation, computer vision, image and speech analysis and the workshop: large-scale visual recognition and machine learning. The second volume has the focus on the following subjects: data mining, bioinformatics, biometrics and medical applications, concurrent and parallel processing, agent systems, robotics and control, artificial intelligence in modeling and simulation and various problems of artificial intelligence.

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