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检索条件"任意字段=17th Image Processing: Algorithms and Systems Conference, IPAS 2019"

共 249 条记录，以下是161-170 订阅

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Digital watermarking method based on image compression algorithms 17th

Digital watermarking method based on image compression algor...

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17th International conference on Next Generation Teletraffic and Wired/Wireless Advanced Networks and systems, NEW2AN 2017, 10th conference on Internet of things and Smart Spaces, ruSMART 2017 and 3rd International Workshop on Nano-scale Computing and Communications, NsCC 2017

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

ISBN: (纸本)9783319673790

Digital watermarking is an efficient method for digital access rights management utilized in the scope of multimedia data. A possibility to combine the procedure of compression and watermarking in effective way for digital images is proposed in this manuscript. this research is focused on the compression methods considering the significance of the initial multimedia object (for example image) different elements to increase the quality of process (compressed) image. One of the most effective approaches for this task is to utilize Error Correcting Codes (ECC) allowing to maintain the number of resulting errors (distortion) as well as the value of resulting compression ratio. the application of such codes enables to distribute errors that are added during the processing procedure according to predefined significance of the initial multimedia object elements. the approach based on Weighted Hamming Metric guarantying the limitation of maximum errors (distortions) with predefined significance is represented as an example. © 2017, Springer International Publishing AG.

关键词： image compression

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Automatic license plate recognition in difficult conditions — Technical report

Automatic license plate recognition in difficult conditions ...

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Joint World Congress of International Fuzzy systems Association and International conference on Soft Computing and Intelligent systems (IFSA-SCIS)

作者： Petr Hurtik Marek Vajgl University of Ostrava Institute for Research and Applications of Fuzzy Modeling Ostrava Czech Republic

ISBN: (纸本)9781509049189

By a car license plate recognition, we mean a software system processing images and providing an alphanumeric transcription of car plates included in an image. We divide the task into four sub-tasks: license plate localization, license plate extraction, characters segmentation and characters recognition. All four sub-tasks are discussed in the context of standard approaches and own solution based on a chain of standard and soft computing image processing algorithms is presented. In this chain, the F-transform approximate pattern matching algorithm plays the crucial role. For the solution, we presented recognition ability for a dataset which includes 500 images with difficult conditions.

关键词： Automobiles Licenses Character recognition Cameras image segmentation image edge detection Transforms

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Real-time smart stereo camera based on FPGA-SoC

Real-time smart stereo camera based on FPGA-SoC

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IEEE-RAS International conference on Humanoid Robots

作者： Soenke Michalik Soeren Michalik Jamin Naghmouchi Mladen Berekovic TU Braunschweig Braunschweig Germany

ISBN: (纸本)9781538646793

Stereo image processing is one of the most demanding tasks in the field of 3D computer vision and robot vision requiring high-performance computing capabilities within embedded systems. Real-time constraints for autonomous vehicles such as humanoid robots, lead to hardware acceleration approaches for high resolution stereo imaging in human-like vision systems, where commonly FPGA device are employed to handle very high sensor data rates. this work presents a realtime smart stereo camera system implementation resembling the full stereo processing pipeline in a single FPGA device. We introduce the novel memory optimized stereo processing algorithm ”Sparse Retina Census Correlation” (SRCC) that embodies a combination of two well established window based stereo matching approaches. We have leveraged a Sum of Absolute Difference (SAD) of Sobel-filtered images and a Sum of Hamming Distance (SHD) using a modified Retina based Census Transform for increased robustness to lighting variations and for high accuracy. A color rectification module has been implemented to cope with the high frame rate of the stereo pipelining calculating image transformations and rectified pixel coordinates in real-time using parameters for camera intrinsic, image rotation, image distortion and image projection. In addition multiple post-processing algorithms like texture filtering, uniqueness filtering, speckle removal and disparity to depth conversion have been implemented to further enhance the output results. the presented smart camera solution has demonstrated real-time stereo processing of 1280×720 pixel depth images with 256 disparities on a Zynq XC7Z030 FPGA device at 60fps. Due to the universal USB3.0 UVC interface and the onboard depth calculation it is a replacement for RGBD 3D-Sensors with improved image quality and outdoor performance. the camera can easily be used in conjunction with ROS-enabled robots and in automotive or industrial applications.

关键词： Field programmable gate arrays Cameras Robot sensing systems Correlation Transforms Real-time systems

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IVOVO: A new interval-valued one-vs-one approach for multi-class classification problems

IVOVO: A new interval-valued one-vs-one approach for multi-c...

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Joint World Congress of International Fuzzy systems Association and International conference on Soft Computing and Intelligent systems (IFSA-SCIS)

作者： Mikel Elkano Mikel Galar Jose Sanz Giancarlo Lucca Humberto Bustince Institute of Smart Cities Public University of Navarre Pamplona Spain

ISBN: (纸本)9781509049189

Decomposition strategies have been shown to be a successful methodology to tackle multi-class classification problems. Among them, One-vs-One approach is a commonly used technique that consists in dividing the original multi-class problem into easier-to-solve binary sub-problems considering each possible pair of classes. However, this methodology is limited to those classifiers returning a single real value for each prediction. In this work, we present a new One-vs-One approach that is able to deal with interval-valued outputs. In order to achieve this goal, we propose applying a normalization method for intervals along with the corresponding extension of three different aggregation strategies: voting, weighted voting, and WinWV. the experimental results show the suitability of the normalization method and the improvement obtained by One-vs-One with respect to a state-of-the-art interval-valued Fuzzy Rule-Based Classification System (IVTURS).

关键词： Pragmatics Training Fuzzy sets Signal to noise ratio image processing Classification algorithms Uncertainty

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Integrated Spoofing Countermeasures and Automatic Speaker Verification: an Evaluation on ASVspoof 2015 17

Integrated Spoofing Countermeasures and Automatic Speaker Ve...

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17th Annual conference of the International-Speech-Communication-Association (INTERSPEECH 2016)

作者： Sahidullah, Md Delgado, Hector Todisco, Massimiliano Yu, Hong Kinnunen, Tomi Evans, Nicholas Tana, Zheng-Hua Univ Eastern Finland Sch Comp Speech & Image Proc Unit Kuopio Finland EURECOM Dept Digital Secur Biot France Aalborg Univ Dept Elect Syst Signal & Informat Proc Aalborg Denmark

ISBN: (纸本)9781510833135

It is well known that automatic speaker verification (ASV) systems can be vulnerable to spoofing. the community has responded to the threat by developing dedicated countermeasures aimed at detecting spoofing attacks. Progress in this area has accelerated over recent years, partly as a result of the first standard evaluation, ASVspoof 2015, which focused on spoofing detection in isolation from ASV. this paper investigates the integration of state-of-the-art spoofing countermeasures in combination with ASV. Two general strategies to countermeasure integration are reported: cascaded and parallel. the paper reports the first comparative evaluation of each approach performed with the ASVspoof 2015 corpus. Results indicate that, even in the case of varying spoofing attack algorithms, ASV performance remains robust when protected with a diverse set of integrated countermeasures.

关键词： Automatic speaker recognition spoofing countermeasures presentation attack detection

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Parallel image dehazing algorithm based on GPU using fuzzy system and hybird evolution algorithm

Parallel image dehazing algorithm based on GPU using fuzzy s...

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ACIS International conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed Computing (SNPD)

作者： Che-Lun Hung Ren-You Yan Hsiao-Hsi Wang Department of Computer Science and Communication Engineering Providence University Taichung Taiwan Department of Computer Science and Information Management Providence University Taichung Taiwan

Haze is an atmospheric phenomenon that fogs the visibility of the scenes. Removing the haze has been an important issue in image processing technologies. Many image dehazing technologies with evolution algorithms have been proposed to remove the fog in the image. However, these algorithms usually are compute-intensive. In this paper, we propose a parallel hybrid evolution algorithm based on GPU to enhance the computational performance. In traditional evolution algorithms, the calculation of fitness function occupies the most of the computation time. In the proposed method, we implement this part on GPU by using CUDA framework to reduce the computational load. the experiment results show that the proposed method can remove the haze efficiently and successfully.

关键词： Graphics processing units Fuzzy systems Evolutionary computation Signal processing algorithms Algorithm design and analysis Genetic algorithms Entropy

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Design and implementation of autonomous mobile device with adaptive control

Design and implementation of autonomous mobile device with a...

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MECHATRONIKA International Symposium

作者： Bohuslava Juhasova Igor Halenar Martin Juhas Faculty of Materials Science and Technology in Trnava Slovak University of Technology in Bratislava Trnava Slovak Republic

ISBN: (纸本)9781509013036

the problem of autonomous vehicles mobility and their orientation in space is an important issue today in the manufacturing sector, especially in relation with the application of standard Industry 4.0. In our paper is presented the design of autonomous mobile device. When designing device, we focused on its wide usability and flexibility in deployment, which was reflected in its architecture. the proposal of device contents necessary sensor system, an important part of the device is system for image processing in real time with sufficient computing capacity. Device computing capacity allows to use more complex control algorithms for orientation in space. Final design include communication channels redundancy for the case of failure of any part of the system. For the implementation of control algorithms was chosen software tool Matlab and its toolbox Simulink.

关键词： Autonomous vehicles Cameras Mobile handsets Robot sensing systems Hardware Aerospace electronics

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Optimal Performance Prediction of ADAS algorithms on Embedded Parallel Architectures 17

Optimal Performance Prediction of ADAS Algorithms on Embedde...

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2015 IEEE 17th International conference on High Performance Computing and Communications (HPCC)

作者： Saussard, Romain Bouzid, Boubker Vasiliu, Marius Reynaud, Roger Renault SAS Guyancourt France Univ Paris 11 Inst Elect Fondamentale Orsay France

ISBN: (纸本)9781479989379

ADAS (Advanced Driver Assistance systems) algorithms increasingly use heavy image processing operations. To embed this type of algorithms, semiconductor companies offer many heterogeneous architectures. these SoCs (System on Chip) are composed of different processing units, with different capabilities, and often with massively parallel computing unit. Due to the complexity of these SoCs, predicting if a given algorithm can be executed in real time on a given architecture is not trivial. In fact it is not a simple task for automotive industry actors to choose the most suited heterogeneous SoC for a given application. Moreover, embedding complex algorithms on these systems remains a difficult task due to heterogeneity, it is not easy to decide how to allocate parts of a given algorithm on the different computing units of a given SoC. In order to help automotive industry in embedding algorithms on heterogeneous architectures, we propose a novel approach to predict performances of image processing algorithms applicable on different types of computing units. Our methodology is able to predict a more or less wide interval of execution time with a degree of confidence using only high level description of algorithms, and a few characteristics of computing units.

关键词： Heterogeneous Architectures Embedded systems Performance Prediction image processing

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Mitosis detection using convolutional neural network based features

Mitosis detection using convolutional neural network based f...

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International Symposium on Computational Intelligence and Informatics

作者： Abdulkadir Albayrak Gokhan Bilgin Department of Computer Engineering Yildiz Technical University Istanbul Turkey

ISBN: (纸本)9781509039104

Breast cancer is the second leading cause of cancer death in women according to World Health Organization (WHO). Development of computer aided diagnostic (CAD) systems has great importance as a secondary reader systems for a correct diagnosis and treatment process. In this paper, a deep learning based feature extraction method by convolutional neural network (CNN) is proposed for automated mitosis detection for cancer diagnosis and grading by histopathological images. the proposed framework is tested on the MITOS data set provided for a contest on mitosis detection in breast cancer histological images released for research purposes in International conference on Pattern Recognition (ICPR'2014). By using provided histopathological images, cellular structures are initially found by combined clustering based segmentation and blob analysis after preprocessing step. then, obtained cellular image patches are cropped automatically from the histopathological images for feature extraction stage. CNN, which is a prominent deep learning method on image processing tasks, is utilized for extracting discriminative features. Due to the high dimensional output of the CNN, combination of PCA and LDA dimension reduction methods are performed respectively for regularization and dimension reduction process. Afterwards, a robust kernel based classifier, support vector machine (SVM), is used for final classification of mitotic and non-mitotic cells. the test results on MITOS data set prove that the proposed framework achieved promising results for mitosis detection on histopathological images.

关键词： Feature extraction image segmentation Breast cancer Neural networks Clustering algorithms Kernel

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Investigating image processing algorithms for Navigating Cultural Heritage Spaces Using Mobile Devices 17th

Investigating Image Processing Algorithms for Navigating Cul...

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17th International conference on Asia-Pacific Digital Libraries (ICADL)

作者： Olojede, Ayodeji Suleman, Hussein Univ Cape Town Dept Comp Sci ZA-7700 Cape Town South Africa

ISBN: (纸本)9783319279749;9783319279732

the use of mobile devices is increasing in the cultural heritage and museum context. the most common approach is to provide a customized mobile device to the museum visitor to navigate museum spaces. In this paper, a mobile cultural heritage guide is presented, which enables image based navigation of rock art sites using computer vision and image processing algorithms for rock art image feature detection and extraction. Traditionally such systems have used algorithms such as Scale-Invariant Feature Transform (SIFT), Speeded-Up Robust Features (SURF) and Oriented Fast and Rotational Brief (ORB). the three algorithms have been integrated in a prototype and their performance has been evaluated. It was observed that digital recognition of rock art images is possible under certain image preprocessing conditions. Also, the evaluation result shows that, generally, SIFT has good accuracy and, when used in conjunction with K Nearest Neighbor, has acceptable matching speed.

关键词： Cultural heritage Rock art images Content based image retrieval system

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