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International conference on Information Communication and Embedded systems (ICICES)

作者： Landge, Amruta Mane, Pranoti MESCOE E&TC Pune Maharashtra India

ISBN: (纸本)9781509025527

Near duplicate image detection needs the matching of a bit altered images to the original image. This will help in the detection of forged images. A great deal of effort has been dedicated to visual applications that need efficient image similarity metrics and signature. Digital images can be easily edited and manipulated owing to the great functionality of image processing software. This leads to the challenge of matching somewhat altered images to their originals, which is termed as near duplicate image detection. This paper discusses the literature reviewed on the development of several image matching algorithms. This paper encompasses 2 sections. Section 1 is the introduction. Section 2 discusses the literature reviewed on the development of image matching algorithms.

关键词： near-duplicate images near-duplicate image retrieval near-duplicate image detection

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image encryption in code based compression algorithms based on multilevel image structure model

Image encryption in code based compression algorithms based ...

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International conference on Ultra Modern Telecommunications and Workshops (ICUMT)

作者： Sergey Bezzateev Natalia Voloshina Saint Petersburg University of Aerospace Instrumentation ITMO University St. Petersburg Russia

image compression is a widely adopted technique used for effective image storage and transmission over open communication channels in cyber-physical systems. Standard cryptographic algorithms are usually used to reach this goal. Therefore, in order to organize effective and secure storage of images it is required to follow two independent and sequential procedures - compression and encryption. In the scenario of interest, it is needed to do compression and encryption transformations in reverse order to restore the original image, i.e. it is necessary to have a so-called “code book” similarly as for encryption and decryption to have a secret key. An effective way of combining these procedures for digital images is proposed in this manuscript. This research is mainly focused on the compression methods that consider significance of the initial multimedia object (for example image) different parts to increase the quality of resulting (decompressed) image. One of the most effective approaches for this task is to utilize error-correcting codes (ECC) that allow to limit the number of resulting errors (distortion) as well as to ensure the value of resulting compression ratio. Application of such codes enable to distribute errors that are added during the processing procedure according to predefined significance of the initial multimedia object elements. The approach that is based on weighted Hamming metric that makes it possible to guaranty the limitation of maximum error number (distortions) that takes into consideration predefined significance of the image zones is represented as an example. The way to use subclass of Goppa codes perfect in weighted Hamming metric when Goppa polynomials are used as a secret key is presented as well. The additional effect of such encrypted compression methods is auto-watermarking of the resulting image.

关键词： image coding Distortion Measurement Error correction codes Encryption Decoding Communication channels

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Some Nonlocal Variational Models Along with Their Fast algorithms 13

Some Nonlocal Variational Models Along with Their Fast Algor...

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13th Web Information systems and Applications conference, WISA 2016

作者： Zheng, Shixiu Pan, Zhengkuan Duan, Jinming Lu, Wenqi Liu, Cunliang Business School of Qingdao University China College of Computer Science and Technology Qingdao University China School of Computer Science University of Nottingham United Kingdom

ISBN: (纸本)9781509054374

Models based on local operators can't preserve texture information. Nonlocal models can be used for many image processing tasks. A main advantage of nonlocal models over classical PDE-based algorithms is the ability to handle textures and repetitive structures. Some nonlocal models along with their Split Bregman algorithms are proposed for image denoising, image inpainting, and image segmentation in this paper. Finally, numerical experiments are shown to validate the efficiency and effectiveness of the proposed models. © 2016 IEEE.

关键词： image segmentation

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HDSVM: A High Efficiency Distributed SVM Framework over Data Stream

HDSVM: A High Efficiency Distributed SVM Framework over Data...

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IEEE International Symposium on Parallel and Distributed processing with Applications and IEEE International conference on Ubiquitous Computing and Communications (ISPA/IUCC)

作者： Yan Hou Yijie Wang Xingkong Ma Li Cheng College of Computer National University of Defense Technology Changsha National Laboratory for Parallel and Distributed Processing China

ISBN: (纸本)9781538637913

The application of Support Vector Machine (SVM) over data stream is growing with the increasing real-time processing requirements in classification field, like anomaly detection and real-time image processing. However, the dynamic live data with high volume and fast arrival rate in data streams make it challenging to apply SVM in data stream processing. Existing SVM implementations are mostly designed for batch processing and hardly satisfy the efficiency requirement of stream processing for its inherent complexity. To address the challenges, we propose a high efficiency distributed SVM framework over data stream (HDSVM), which consists of two main algorithms, incremental learning algorithm and distributed algorithm. Firstly, we propose a partial support vectors reserving incremental learning algorithm (PSVIL). By selecting a subset of support vectors based on their distances to classification hyperplane instead of the universal set to update SVM, the algorithm achieves lower time overhead while ensuring accuracy. Secondly, we propose a distribution remaining partition and fast aggregation distributed algorithm (DRPFA) for SVM. The real-time data is partitioned based on the original distribution with clustering instead of random partition, and historical support vectors are partitioned based on their distances to the classification hyperplane. The global hyperplane can be obtained by averaging the parameters of local hyperplanes due to the above partition strategy. Extensive experiments on Apache Storm show that the proposed HDSVM achieve lower time overhead and similar accuracy compared with the state-of-art. Speed-up ratio is increased by 2-8 times within 1% accuracy deviation.

关键词： Support vector machines Training Distributed databases Distributed algorithms Real-time systems Partitioning algorithms Streaming media

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Parallel image processing on the Sunway Many-core Processor

Parallel Image Processing on the Sunway Many-core Processor

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18th IEEE International conference on High Performance Computing and Communications (HPCC) / 14th IEEE International conference on Smart City (Smart City) / 2nd IEEE International conference on Data Science and systems (DSS)

作者： Zhao, Meiting Liu, Rui Liu, Yi Song, Kaida Qian, Depei Beihang Univ Sinogerman Joint Software Inst Beijing Peoples R China State Key Lab Math Engn & Adv Comp Wuxi Peoples R China

ISBN: (纸本)9781509042975

Many image processing algorithms have been parallelized successfully on many-core processors, such as GPU and Intel Xeon Phi. In this paper, we choose the Sunway many-core processor SW26010, which is a new processor designed and made in China that constitutes the current NO. 1 supercomputer Sunway TaihuLight. This paper firstly introduces the architecture of Sunway SW26010 processor and two representative image processing algorithms: local binary pattern (LBP) and histogram of oriented gradient (HOG). Furthermore we propose a method of parallel implementation, and the experimental results of this method show that the speedup can be up to 170 for LBP and 33 for HOG. Then two optimized methods are brought forward based on this parallel implementation, including the optimization of program and parallel design. We optimize the program by using the method that combined step transmission and software prefetching. From the experiment results of the first optimization we can know that the maximum speedup can reach 310 for LBP with processing high-resolution images and 83 for HOG. Then we optimize the parallel design by using a coarse grained parallel method, and the experimental results show that the speedup can be up to 370 for LBP and 95 for HOG when processing low-resolution images. Finally, we investigate the scalability of our parallelism on the Sunway TaihuLight with different number of processor nodes, and the experiment results prove that the two algorithms' parallel design and implementation have better expansibility.

关键词： image processing Sunway SW26010 processor the Sunway TaihuLight supercomputer parallel implementation optimization

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Impact of interactivity on the assessment of quality of experience for light field content

Impact of interactivity on the assessment of quality of expe...

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International Workshop on Quality of Multimedia Experience, QoMEx

作者： Irene Viola Martin Řeřábek Touradj Ebrahimi EPFL Multimedia Signal Processing Group Lausanne Switzerland

The recent advances in light field imaging are changing the way in which visual content is captured, processed and consumed. Storage and delivery systems for light field images rely on efficient compression algorithms. Such algorithms must additionally take into account the feature-rich rendering for light field content. Therefore, a proper evaluation of visual quality is essential to design and improve coding solutions for light field content. Consequently, the design of subjective tests should also reflect the light field rendering process. This paper aims at presenting and comparing two methodologies to assess the quality of experience in light field imaging. The first methodology uses an interactive approach, allowing subjects to engage with the light field content when assessing it. The second, on the other hand, is completely passive to ensure all the subjects will have the same experience. Advantages and drawbacks of each approach are compared by relying on statistical analysis of results and conclusions are drawn. The obtained results provide useful insights for future design of evaluation techniques for light field content.

关键词： image coding Visualization Imaging image resolution image color analysis Software Temperature measurement

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Comparison of Turbulence Mitigation algorithms

Comparison of Turbulence Mitigation Algorithms

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conference on Long-Range Imaging

作者： Kozacik, Stephen Paolini, Aaron Bonnett, James Kelmelis, Eric EM Photon 51 East Main StSuite 203 Newark DE 19711 USA

ISBN: (纸本)9781510600874

When capturing image data over long distances (0.5 km and above), images are often degraded by atmospheric turbulence, especially when imaging paths are close to the ground or in hot environments. These issues manifest as time-varying scintillation and warping effects that decrease the effective resolution of the sensor and reduce actionable intelligence. In recent years, several image processing approaches to turbulence mitigation have shown promise. Each of these algorithms have different computational requirements, usability demands, and degrees of independence from camera sensors. They also produce different degrees of enhancement when applied to turbulent imagery. Additionally, some of these algorithms are applicable to real-time operational scenarios while others may only be suitable for post-processing workflows. EM Photonics has been developing image-processing-based turbulence mitigation technology since 2005 as a part of our ATCOM [1] image processing suite. In this paper we will compare techniques from the literature with our commercially-available real-time GPU accelerated turbulence mitigation software suite, as well as in-house research algorithms. These comparisons will be made using real, experimentally-obtained data for a variety of different conditions, including varying optical hardware, imaging range, subjects, and turbulence conditions. Comparison metrics will include image quality, video latency, computational complexity, and potential for real-time operation.

关键词： image fusion Turbulence Reconstruction algorithms Speckle Deconvolution image processing Cameras Imaging systems image quality Photonics

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Edge detection based on Retinex theory and wavelet multiscale product for mine images

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APPLIED OPTICS 2016年第34期55卷 9625-9637页

作者： Du, Yuxin Tong, Minming Zhou, Lingling Dong, Haibo China Univ Min & Technol Sch Informat & Elect Engn Xuzhou 221008 Peoples R China

The application of visual technology to mine robots has become a hot topic in the development of coal mine automatic production. Key techniques of robot control are the feature recognition of sampled videos and the perception of complex surroundings. However, it is difficult for features in underground images with dark hue and low target discrimination to be recognized and extracted, especially for reasons of the nonuniform illumination and heavy dust concentration in mines. Hence, an edge detection algorithm based on the Retinex theory and wavelet multiscale product is proposed in this paper for low-light-level mine image feature extraction, which employs a modified multiscale Retinex method to deal with the low frequency subplot after the wavelet decomposition, an improved fuzzy enhancement approach to handle high frequency components, and finally a revised multiscale product edge detection algorithm to obtain the ultima edge image. Compared with a variety of algorithms by detecting edges of both normal illuminated and underground images, experimental results show that with characteristics of high real-time performance and detection accuracy, the proposed algorithm can exactly meet the needs of surrounding environment perception for mine robots, which applies well to image edge detection in low illumination mines. (C) 2016 Optical Society of America

关键词： Digital image processing Edge detection Feature extraction Fourier transforms image processing Optical control systems

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BACKGROUND PRIOR AND BOUNDARY WEIGHT-BASED PEDESTRIAN SEGMENTATION IN INFRARED imageS 23

BACKGROUND PRIOR AND BOUNDARY WEIGHT-BASED PEDESTRIAN SEGMEN...

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23rd IEEE International conference on image processing (ICIP)

作者： Li, Lu Zheng, Yu Bai, Xiangzhi Zhou, Fugen Beihang Univ Image Proc Ctr Beijing 100191 Peoples R China

ISBN: (纸本)9781467399616

Pedestrian segmentation in infrared images is a difficult problem for the defects of low SNR and inhomogeneous luminance distribution. In this paper, we propose a method which aims to obtain the accurate pedestrian segmentation through a background prior and boundary weight-based saliency. Background likelihood is firstly calculated as background prior to get an abstract representation for infrared pedestrian. Then, by considering the object-center prior, the object-biased Gaussian model is applied to derive the probability density estimation for pedestrians. Finally, the above two results are integrated with the boundary weight to obtain the final saliency map for infrared image, based on which pedestrians can be easily segmented. Experimental results on real infrared images captured by intelligent transportation systems demonstrate the effectiveness of the proposed approach against the state-of-the-art algorithms.

关键词： infrared image saliency pedestrian segmentation background prior

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Automatic Safety Helmet Wearing Detection

Automatic Safety Helmet Wearing Detection

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IEEE International conference on Cyber Technology in Automation, Control, and Intelligent systems

作者： Kang Li Xiaoguang Zhao Jiang Bian Min Tan The State Key Laboratory of Management and Control for Complex System University of Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781538604915

Surveillance is very essential for the safety of power substation. The detection of whether wearing safety helmets or not for perambulatory workers is the key component of overall intelligent surveillance system in power substation. In this paper, a novel and practical safety helmet detection framework based on computer vision, machine learning and image processing is proposed. In order to ascertain motion objects in power substation, the ViBe background modelling algorithm is employed. Moreover, based on the result of motion objects segmentation, real-time human classification framework C4 is applied to locate pedestrian in power substation accurately and quickly. Finally, according to the result of pedestrian detection, the safety helmet wearing detection is implemented using the head location, the color space transformation and the color feature discrimination. Extensive compelling experimental results in power substation illustrate the efficiency and effectiveness of the proposed framework.

关键词： Safety Substations Feature extraction image color analysis Support vector machines Surveillance Classification algorithms

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