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International Journal of Control and Automation 2015年第9期8卷 303-312页

作者： Li, Meng Cai, Zemin Wei, Chuliang Yuan, Ye Department of Electronic Engineering College of Engineering Shantou University China Guangdong Provicial Key Laboratory of Digital Signal and Image Processing TechniquesChina China

Due to the numerous important applications of video surveillance and monitoring, video object tracking has been an active research topic in the last decade. This paper makes a survey of approaches to high quality object tracking by looking at theoretical backgrounds and practical results, which are categorized into four groups. The principle, the evolution processes and the latest progresses of these approaches are identified to form a conclusion for future directions of object tracking algorithms © 2015 SERSC.

关键词： Surveys

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Handwritten signature verification using Hidden Markov Models

Handwritten signature verification using Hidden Markov Model...

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2012 International Conference on image processing, Computer Vision, and Pattern Recognition, IPCV 2012

作者： Khachaturyan, Vahe Digital Signal and Image Processing Laboratory Institute for Informatics and Automation Problems Yerevan Armenia

ISBN: (纸本)9781601322258

In this paper we present the work developed on off-line signature verification using Hidden Markov Models (HMM)[1]. HMM is a well-known technique used by other biometric features, for instance, in speaker recognition and dynamic or on-line signature verification. Our goal here is to extend Left-to-Right (LR)-HMM to the field of static or off-line signature processing using results provided by image connectivity analysis. The chain encoding of perimeter points for each blob obtained by this analysis is an ordered set of points in the space, clockwise around the perimeter of the blob. We discuss two different ways of generating the models depending on the way the blobs obtained from the connectivity analysis are ordered. Finally, two LR-HMM models are trained using the parameters obtained by the mentioned techniques. Verification results of the two techniques are compared and some improvements are proposed.

关键词： Hidden Markov models

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On a dualband rectangular dielectric resonator antenna for WLAN applications 5

On a dualband rectangular dielectric resonator antenna for W...

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5th IEEE International Conference on Computational Electromagnetics, ICCEM 2019

作者： Xiaosheng, Fang Shuangming, Chen Lingpeng, Weng Guangdong Provincial Key Laboratory of Digital Signal and Image Processing Shantou University Shantou China

ISBN: (纸本)9781538671115

A slot-fed dualband rectangular dielectric resonator antenna (DRA) for WLAN applications is investigated. ANSYS HFSS was used to study the reflection coefficient, radiation patterns and antenna gain of the dualband DRA. The results show that it can provide two passbands in the ranges of 2.4-2.82 GHz and 5.07-5.54 GHz, which completely cover the 2.4-GHz/5.2-GHz WLAN bands. The proposed dualband DRA can provide a relatively larger high-to-low frequency ratio of ~2.1. © 2019 IEEE.

关键词： Microwave antennas

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Prediction of chaotic EEG signal using multiple wavelet neural network

Prediction of chaotic EEG signal using multiple wavelet neur...

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2013 International Conference on Human Health and Medical Engineering, HHME 2013

作者： Sun, Lisha Huang, Fei Key Laboratory of Digital Signal and Image Processing of Guangdong Province Shantou University Guangdong China

ISBN: (纸本)9781845648923

In this paper we proposed a new method to approximate and reveal the essential piecewise chaos dynamics characteristics of EEG more effectively than the conventional single neural network model. The simulation with the real EEG signal proves the effectiveness of the proposed model. At last, we used the multiple wavelet neural networks to detect epilepsy in normal EEG signal;the result shows that the proposed model is an effective epilepsy detector. © 2014 WIT Press.

关键词： Neurology

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Global-local feature attention network with reranking strategy for image caption generation

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Optoelectronics Letters 2017年第6期13卷 448-451页

作者：吴捷谢斯雅史新宝陈耀文 College of Engineering Shantou University Shantou 515063 China Key Laboratory of Digital Signal and Image Processing of Guangdong Shantou University Shantou 515063 China

In this paper, a novel framework, named as global-local feature attention network with reranking strategy(GLAN-RS), is presented for image captioning task. Rather than only adopting unitary visual information in the classical models, GLAN-RS explores the attention mechanism to capture local convolutional salient image maps. Furthermore, we adopt reranking strategy to adjust the priority of the candidate captions and select the best one. The proposed model is verified using the Microsoft Common Objects in Context(MSCOCO) benchmark dataset across seven standard evaluation metrics. Experimental results show that GLAN-RS significantly outperforms the state-of-the-art approaches, such as multimodal recurrent neural network(MRNN) and Google NIC, which gets an improvement of 20% in terms of BLEU4 score and 13 points in terms of CIDER score.

关键词： capture unitary salient adopt benchmark verified Context priority sentences candidate

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High speed fingerprint recognition method

High speed fingerprint recognition method

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2nd International Conference on Multimedia Technology, ICMT 2011

作者： Kocharyan, Davit Sarukhanyan, Hakob Digital Signal and Image Processing Laboratory Institute for Informatics and Automation Problems of NAS RA Yerevan Armenia

ISBN: (纸本)9781612847740

In this paper we intend to propose a high-speed method for fingerprint recognition based on minutiae matching, which, unlike conventional minutiae matching algorithms, also takes into account region and line structures that exist between minutiae pairs, allowing getting more structural information of the fingerprint and resulting in stronger and more accurate matching of minutiae. © 2011 IEEE.

关键词： image processing

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Wideband and Replaceable Cylindrical Dielectric Resonator Antennas

Wideband and Replaceable Cylindrical Dielectric Resonator An...

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2020 IEEE MTT-S International Microwave Workshop Series on Advanced Materials and Processes for RF and THz Applications, IMWS-AMP 2020

作者： Weng, Ling Peng Fang, Xiao Sheng Yan, Jing Shi, Kang Ping Guangdong Provincial Key Laboratory of Digital Signal and Image Processing Department of Electronic and Information Engineering Shantou China

ISBN: (纸本)9781728160641

A wideband and replaceable dielectric resonant antenna (DRA) excited by a probe is investigated. The proposed wideband DRA consists of a probe platform and a solid cylindrical dielectric resonator, and two magnets are applied to fix them. In this way, the dielectric resonator can be easily replaced. Therefore, three kinds of wideband DRAs with impedance bandwidth of 35.8%, 56.6% and 74% are designed. The reflection coefficient, radiation mode and antenna gain of the cylindrical DRA were analyzed by using HFSS ANSYS. © 2020 IEEE.

关键词： Microwave antennas

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Flow Visualization for Complex Fluid Flows via A Structure-enhanced Motion Estimator

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IEEE Transactions on Circuits and Systems for Video Technology 2025年

作者： Chen, Jun Wang, He Hao, Zhifeng Cai, Zemin Mei, Ling Foshan University School of Industrial Design and Ceramic Art Foshan528000 China Foshan University school of Mechatronic Engineering and Automation Foshan528231 China Shantou University College of Science Department of Mathematics Guangdong 515063 China Shantou University Department of Electronic Engineering Guangdong Shantou515063 China Guangdong Provincial Key Laboratory of Digital Signal and Image Processing Techniques Guangdong Shantou515063 China Wuhan University of Science and Technology School of Information Science and Engineering 430081 China Huazhong University of Science and Technology School of Artificial Intelligence and Automation 430074 China Western Michigan University Department of Mechanical and Aerospace Engineering KalamazooMI49008 United States

Flow visualization through motion estimation using time-sequenced images plays a significant role in analyzing and understanding complex flow phenomena, and it is widely used in meteorology, oceanography, medicine, astronomy, experimental fluid mechanics, etc. However, it is difficult for current motion estimators to adapt to illumination changes, remove instable perturbation, and capture diverse motion patterns. In this paper, a novel flow visualization tool is developed to address these issues by employing a structure-enhanced motion estimator composed of a data term and a regularization term. Specifically, a statistical correlation descriptor is designed for the data term to improve the accuracy of motion estimation by enhancing both illumination robustness and matching discrimination. Inspired by the strong distinguishability of a structure-texture distribution in a local window, a structure-enhanced regularizer that considers the physical mechanism of fluid diffusion is introduced to capture different motion patterns, enhance prominent flow structures, and remove unnecessary ripples or textures caused by instable perturbation or noise. The experimental results demonstrate that our approach significantly outperforms current motion estimators in handling illumination changes and predicting complex fluid flows, and it also achieves state-of-the-art evaluation results on the public fluid flow datasets. Furthermore, the designed flow visualization tool successfully captures diverse motion patterns in Jupiter’s White Ovals, which is crucial for understanding the physical mechanisms behind their formation and sustenance. © 1991-2012 IEEE.

关键词： Motion estimation

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Automatic Pavement Crack Detection Based on YOLOv5-AH 12

Automatic Pavement Crack Detection Based on YOLOv5-AH

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12th International Conference on CYBER Technology in Automation, Control, and Intelligent Systems, CYBER 2022

作者： Dong, Zhaohui Zhu, Guijie Fan, Zhun Liu, Jiacheng Li, Huanlin Cai, Yuwei Huang, Huaxing Shi, Ze Ning, Weibo Wang, Liu Guangdong Provincial Key Laboratory of Digital Signal and Image Processing College of Engineering Shantou University Shantou515063 China

ISBN: (数字)9781665472678

ISBN: (纸本)9781665472678

Object detection on pavement cracks plays a significant role in the overall condition assessment of the pavement. However, the automatic crack detection remains a tough work due to the complex background and the scale change. In order to solve the related issues, a deep learning model named YOLOv5-AH is proposed on the basis of the YOLOv5. We integrate convolutional block attention module (CBAM) to extract attention area, which can emphasize the crack features and suppress the background information. Moreover, we optimize the network architecture by adding one more prediction head to detect different-scale cracks. To further improved our proposed YOLOv5-AH, a series of advanced strategies are integrated into the model training including data augmentation. A pavement crack dataset in different enviroments is built by a mobile robot. The precision and recall of our crack detection method reach 0.924 and 0.988 respectively. The prediction speed of the model can achieve real-time effect (72FPS). © 2022 IEEE.

关键词： Crack detection

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Corona noise characteristics in high voltage PLC channel

Corona noise characteristics in high voltage PLC channel

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2003 IEEE International Conference on Industrial Technology, ICIT - Proceedings

作者： Suljanović, Nermin Mujčić, Aljo Zajc, Matej Tasič, Jurij F. Laboratory for Digital Signal Image and Video Processing Faculty of Electrical Engineering Ljubljana Trzaska 25 1000 Ljubljana Slovenia

The paper presents the algorithm for estimation of frequency and time characteristics of the corona noise in high voltage power-line carrier (PLC) communications. In the frequency domain corona noise is represented with power spectral density and with Gaussian noise voltage with variable root mean square (RMS) value in time domain. The analytic method for estimation of the corona noise appearing at the line terminals in frequency and time domain is given. Simulations results are compared with the measurements on actual 400 kV power line. © 2003 IEEE.

关键词： Electric lines

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