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The Marked-line Recognition Based on Network Topology Diagram Points Clustering

The Marked-line Recognition Based on Network Topology Diagra...

引用

ieee symposium Series on computational intelligence (SSCI)

作者： Chen, Xianyi Peng, Xiafu Wang, Sun'an Xiamen Univ Dept Automat Xiamen 361005 Fujian Peoples R China Xi An Jiao Tong Univ Sch Mech Engn Xian 710049 Shanxi Peoples R China

ISBN: (纸本)9781728124858

Marked-line recognition is one of the important methods to realize the patrol Automatic Guided Vehicle (AGV) autonomous navigation. This paper will focus on a new method in marked-line recognition and it has good robustness in outdoor environment which the illumination is variation, the marked-line is partially-occluded, and the objects on the load are similar to the marked-line. Firstly, the feature points of the marked-line are extracted by using the color and contour features, and the feature points are used as vertexes to construct the network topological diagram G = (V, E). Secondly, the vertexes are clustered by using the slope and the slope change rate of the network edges, and the vertexes of each clustering are connected by polylines. Lastly, the subclasses are clustered again if the average slope and the average slope change rate of each subclass are similar. The class with the most vertexes is used to recognize marked-line. The experimental result demonstrates that the recognition accuracy is almost 100% under the variant illumination intensity and even if the marked-line with partial occlusion the recognition accuracy is about 98.5%, the experimental results show that the method has good robustness in complex outdoor environment. In addition, the method takes about 45ms and it has good real time performance.

关键词： marked-line recognition image processing feature point clustering AGV

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AUTOMATIC RADIOGRAPHIC QUANTIFICATION OF JOINT SPACE NARROWING PROGRESSION IN RHEUMATOID ARTHRITIS USING POC 16

AUTOMATIC RADIOGRAPHIC QUANTIFICATION OF JOINT SPACE NARROWI...

引用

16th ieee International symposium on Biomedical Imaging (ISBI)

作者： Ou, Yafei Ambalathankandy, Prasoon Shimada, Takeshi Kamishima, Thmotsu Ikebe, Masayuki Hokkaido Univ Res Ctr Integrated Quantum Elect Sapporo Hokkaido Japan Hokkaido Univ Grad Sch Hlth Sci Sapporo Hokkaido Japan

ISBN: (纸本)9781538636411

This paper is an application of image processing techniques for computer-aided diagnosis of Rheumatoid Arthritis (RA). Accurately measuring the progression of joint space narrowing (JSN) is crucial during medical treatment and in imaging biomarkers in clinical trials. In this paper, we analyze sequential radiographic images of patients who have rheumatoid arthritis in hands using image processing techniques. Phase only correlation (POC) is used to detect the progression of JSN between images. A new image processing algorithm is proposed to segment joint images so as to eliminate the mutual interference when measuring the movement of the upper and lower hones by POC. We found that the texture feature on bones will greatly affect the accuracy of POC. Median filter is used to eliminate the effect of texture, and excellent results are obtained in practice. Additionally, the progress of JSN is measured accurately in our method. This can be beneficial for doctors in the identification of disease stages.

关键词： Rheumatoid arthritis Progression of joint space narrowing Phase only correlation Computer-aided diagnosis Automatic quantification image segmentation

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Safe Human-Computer Interface Based On Efficient image processing Algorithm

Safe Human-Computer Interface Based On Efficient Image Proce...

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International symposium on computational intelligence and Informatics

作者： S. Wilding P. Walker S. Clinton D. Williams J. I. Olszewska University of West Scotland UK

ISBN: (数字)9781728183404

ISBN: (纸本)9781728183411

With the growing digitalization of our society and the increasing development of Industry 4.0, the development of safe human-computer interfaces is of prime importance. For this purpose, we present a new solution for avoiding any physical contact between the human and the machine's display and/or its keyboard/pad. Hence, we developed an innovative image processing algorithm which runs on the live video stream of the remote interaction between the human and the machine such as a computer or an intelligent agent; the video stream being captured by an off-the-shelf camera which is embedded in the main machine. The resulting computer-vision system performs visual object detection and tracking of a marker the user holds in one hand and could wave it from a distance in order to remotely interact with the interface of the machine. This remote interaction system has been successfully tested in real-world operational conditions, and the performance of this image processing application has been evaluated in real time.

关键词： Human computer interaction Task analysis Webcams image color analysis Safety Streaming media Real-time systems

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Generation of Natural Traffic Sign images Using Domain Translation with Cycle-Consistent Generative Adversarial Networks 30

Generation of Natural Traffic Sign Images Using Domain Trans...

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30th ieee Intelligent Vehicles symposium (IV)

作者： Spata, Dominic Horn, Daniela Houben, Sebastian Ruhr Univ Bochum Inst Neural Computat Univ Str 150 D-44801 Bochum Germany

ISBN: (纸本)9781728105604

Video-based traffic sign recognition poses a highly challenging problem due to the significant number of possible classes and large variances of recording conditions in natural environments. Gathering an appropriate amount of data to solve this task with machine learning techniques remains an overall issue. In this study, we assess the suitability of automatically generated traffic sign images for training corresponding image classifiers. To this end, we adapt the recently proposed cycle consistent generative adversarial networks in order to transfer automatically rendered prototypical traffic sign images for which we control type, pose, and to a degree background into their true-to-life counterparts. We test the proposed system by extensive experiments on the German Traffic Sign Recognition Benchmark dataset Ill and learn that both a HOG feature-based SVM classifier and a state-of-the-art CNN exhibit reasonable performance when solely trained on artificial data. Consequently, it is well suited as data augmentation method and allows for covering uncommon cases and classes.

关键词： convolutional neural nets feature extraction image classification learning (artificial intelligence) object detection object recognition support vector machines traffic engineering computing video signal processing traffic signs Video signal processing Object detection Support Vector Network image classification object recognition Feature extraction engineering computing images

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An Efficient Seizure Prediction Method Based on Multi-scale Feature Fusion with Reduced Channels

An Efficient Seizure Prediction Method Based on Multi-scale ...

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symposium of image, signal processing, and Artificial Vision (STSIVA)

作者： Shunxian Gu Xinning Song College of Computer and Information Hohai University Nanjing China

ISBN: (纸本)9781665426565

Epilepsy is one of the most common neurological diseases worldwide as a common mental disorder. Seizure prediction plays a vital role in improving a patient’s quality of life. This paper proposes a patient-specific seizure prediction method based on multi-scale feature fusion. This study aims at developing an efficient and automatic seizure prediction technique by raw scalp EEG signals with reduced channels. The proposed approach utilizes the deep convolutional neural network in noise handling and the recurrent neural network in establishing contextual correlation. Not any manual feature engineering is performed on the raw EEG data. A multi-scale fusion approach based on the downsampling technique is introduced to compensate for the performance degradation problem caused by reduced channels. 2 is proven to be the best view number. Our proposed C-Bi-LSTM model with multi-views provides the highest overall accuracy of 99.597% and the lowest false positive rate of 0.004 per hour by comparing the classification results.

关键词： Degradation Correlation Sensitivity Recurrent neural networks computational modeling Scalp Predictive models

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SALIENCY computational MODEL FOR FOGGY imageS BY FUSING FREQUENCY AND SPATIAL CUES 26

SALIENCY COMPUTATIONAL MODEL FOR FOGGY IMAGES BY FUSING FREQ...

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26th ieee International Conference on image processing (ICIP)

作者： Xu, Xin Zhu, Xin Mu, Nan Chen, Li Tian, Jing Wuhan Univ Sci & Technol Sch Comp Sci & Technol Wuhan 430065 Peoples R China Wuhan Univ Sci & Technol Hubei Prov Key Lab Intelligent Informat Proc & Re Wuhan 430065 Peoples R China Wuhan Univ Sci & Technol Artificial Intelligence Inst Wuhan 430065 Peoples R China

ISBN: (纸本)9781538662496

A key challenge of saliency computation in foggy images is how to effectively detect salient objects which are less visible. The primary cause may lie in the fact that the light scattering through fog particles reduces image contrast. In this paper, we propose a frequency-spatial fusion saliency computational model based on discrete stationary wavelet transform (DSWT). The input image is firstly transformed into HSV color space, and the amplitude spectrum of each color channel is adjusted to generate the frequency domain saliency map. Then, the local-global superpixel contrast is measured to obtain the spatial domain saliency map. The DSWT is finally utilized to fuse the frequency-spatial cues. Experimental results indicate that the proposed model can efficiently reduce the influence of light scattering through fog particles, and can achieve the best performance in foggy images comparing to 16 state-of-the-art saliency models.

关键词： Saliency Computation Frequency Domain Spatial Domain Discrete Stationary Wavelet Transform Foggy image

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A COMPARISON BETWEEN image AND signal SHARPNESS-BASED AXIAL LOCALIZATION OF ULTRASOUND SCATTERERS 16

A COMPARISON BETWEEN IMAGE AND SIGNAL SHARPNESS-BASED AXIAL ...

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16th ieee International symposium on Biomedical Imaging (ISBI)

作者： Diamantis, Konstantinos Dalgarno, Paul A. Anderson, Tom Jensen, Jorgen Arendt Sboros, Vassilis Univ Edinburgh Inst Digital Commun Edinburgh EH9 3FG Midlothian Scotland Heriot Watt Univ Sch Engn & Phys Sci Edinburgh EH14 4AS Midlothian Scotland Univ Edinburgh Ctr Cardiovasc Sci Edinburgh EH16 4TJ Midlothian Scotland Tech Univ Denmark Ctr Fast Ultrasound Imaging DK-2800 Lyngby Denmark

ISBN: (纸本)9781538636411

Super-resolution ultrasound imaging deploys contrast microbubble (MB) tracking to delineate micro-vessels. The potential application spans to a large number of diseases which cause compromised vascular networks. Current super resolution methods are mainly based on image processing. Sharpness-based localization is an alternative to such methods for scatterer localization in the axial direction, and can be implemented using both image and signal data. A 7-MHz, linear ultrasound transducer (lambda=212 mu m) and the Synthetic Aperture Real-time Ultrasound System (SARUS) were used to image a wire-target (point scatterer) at different depth positions. The method predicts a depth estimate and its difference from the true scatterer position demonstrates its accuracy. This average difference can be as low as 27.41 mu m (or approximate to lambda/8) for the image-derived sharpness and drops to 2.84 mu m (or approximate to lambda/75) when the signals are used. These figures were calculated for a 8 mm depth range, which can be extended subject to further processing. The process of image formation involves interpolation and logarithmic compression that reduce the overall performance of the method when using image data. Such details may be significant when reconstructing micro-vessels of the order of tens of micrometres in diameter.

关键词： Axial localization multiple focusing sharpness super-resolution ultrasound ultrasound scatterers

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CLOSED-FORM EXPRESSION OF THE FOURIER RING-CORRELATION FOR SINGLE-MOLECULE LOCALIZATION MICROSCOPY 16

CLOSED-FORM EXPRESSION OF THE FOURIER RING-CORRELATION FOR S...

引用

16th ieee International symposium on Biomedical Imaging (ISBI)

作者： Thanh-an Pham Soubies, Emmanuel Sage, Daniel Unser, Michael Ecole Polytech Fed Lausanne Biomed Imaging Grp CH-1015 Lausanne Switzerland

ISBN: (纸本)9781538636411

Single-molecule localization microscopy (SMLM) is a popular microscopic technique that achieves super resolution imaging by localizing individual blinking molecules in thousands of frames. Therefore, the reconstructed high-resolution image is a combination of millions of point sources. This particular computational reconstruction leads to the question of the estimation of the image resolution. Fourier-ring correlation (FRC) is the standard tool for assessing the resolution. It has been proposed for SMLM by computing a discrete correlation in the Fourier domain. In this work, we derive a closed-form expression to compute the continuous FRC. Our implementation provides an exact ERG and an alternative to compute a parameter-free FRC. In addition, it gives insights on the discrepancy of the discrete FRC and yields a rule to select its parameters such as the spatial sampling step or the width of the kernel used as density estimator.

关键词： Single-molecule local ring correlation image resolution

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Improving Neural Network Architecture Compression by Multi-Grain Pruning

Improving Neural Network Architecture Compression by Multi-G...

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symposium of image, signal processing, and Artificial Vision (STSIVA)

作者： Kevin Kollek Miguel Angel Aguilar Marco Braun Anton Kummert School of Electrical Information and Media Engineering University of Wuppertal Wuppertal Germany Aptiv Services Deutschland GmbH Wuppertal Germany

ISBN: (纸本)9781665426565

Pruning techniques for neural networks are applied to achieve superior model compression while maintaining accuracy. Common pruning approaches rely on single granularity (e.g., weights, channels, or layers) compression techniques and miss valuable optimization potential. This major limitation results in a sequence of obsolete layers with a small number of channels or highly sparse weights. In this paper, we present a novel pruning approach to address this issue. More precisely, in this work, a Multi-Grain Pruning (MGP) framework is proposed to optimize neural network architectures from coarse to fine in up to four different granularities. Besides the traditional pruning granularities, a new granularity is introduced on so-called blocks, which consist of multiple layers. By combining multiple pruning granularities, models can be optimized even further. We evaluated the proposed framework with VGG-19 on CIFAR-10 and CIFAR-100 as well as ResNet-56 on CIFAR-10 and ResNet-50 on imageNet. The results show that our technique achieves from 31.9x up to 185.3x model compression rates with an accuracy drop from 0.08% up to 1.73% with VGG-19 on CIFAR-10.

关键词： image coding computational modeling Conferences Neural networks Computer architecture Informatics Optimization

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Improving the Hough Transform Through Three New Morphological Operators

Improving the Hough Transform Through Three New Morphologica...

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International Conference on Artificial intelligence and Data processing (IDAP)

作者： Baykal, Ibrahim Cem Adana AT Sci & Technol Univ Comp Engn Dept Adana Turkey

ISBN: (纸本)9781728129334;9781728129327

Despite being one of the most famous line detectors, Hough Transform has reliability issues. Hough Transform works better on long lines. This article introduces three new binary morphological operators that stretches binary edge images. The first of these operators thins the output of the binary edge image so that the second one can stretch it. The third operator, smooth, is designed for smoothing the lines that are stretched. Results show that these two operators improve Hough Transform results considerably at a very low computational expense. The author publicly shared the executable of the algorithm and the dataset on the Github to prove the efficiency of the method.

关键词： image processing Hough Transform morphologic operator line detector circle detector OpenCV

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