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9th International Conference on image and Signal Processing, ICISP 2020

作者： El Baz, Manal Zaki, Taher Douzi, Hassan Image and Pattern Recognition - Intelligent and Communicating Systems Laboratory Faculty of Sciences Ibn Zohr University Agadir Morocco

ISBN: (纸本)9783030519346

Detection of elliptical features is a challenging and important task in computer vision. In fact, ellipses can describe many objects in real images like manufactured objects, cells, ball, or traffic signs. Furthermore, an ellipse is defined by five parameters: the center coordinates, the semi major axe, the semi minor axe and the orientation, which require more computational power to estimate them. Some non-ideal ellipses cause also difficulties for detection such as occlusion, appearance of multiple ellipses at same time and non-parallel ellipse. In this paper, we are interested in detecting elliptical traffic signs. We present a method for detecting different cases of ellipses: simple, partially occluded, non-parallel, multiple ellipses in images. The method selects three lines to find the ellipse center, and then it calculates the value of the semi minor and major axes of the ellipse. Experiments show that the proposed method performs well on real images in the presence or not of noises. © Springer Nature Switzerland AG 2020.

关键词： Binary images

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An Improved Method for Red Segmentation Based Traffic Sign Detection

An Improved Method for Red Segmentation Based Traffic Sign D...

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International Conference on Information, Communication and Networks (ICICN)

作者： Manal El Baz Taher Zaki Hassan Douzi Image and Pattern Recognition – Intelligent and Communicating Systems Laboratory Faculty of Sciences Ibn Zohr University Agadir Morocco

ISBN: (纸本)9781665411578

The red color segmentation is widely used in image processing especially for traffic sign detection. The color segmentation under variety of light and weather conditions is a challenging task. These conditions make modifications on traffic sign colors. In this paper, we aim to improve the precision of a state-of-the-art method in RGB and HSV spaces. Although the efficiency of this state-of-the-art method, the red segmentation in RGB space has some false positive detections especially at night, and the red segmentation in HSV space detects the black pixels with red pixels as a region of interest. In order to improve the precision of this method, we propose in this paper to combine the two segmentations. We also propose changing the threshold of the red segmentation in HSV to remove non-red pixels and to extract red pixels with low saturation. In addition, we make some modifications on the threshold of the red segmentation in RGB space to improve its performance. The results obtained in experiments show that our method detects more accurately red color of traffic signs under variety of light and weather conditions compared to the state-of-the-art method.

关键词： image segmentation image color analysis Conferences Color Task analysis Meteorology

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Modeling, multi agent approach and tools for decision support systems applied urban road traffic

Modeling, multi agent approach and tools for decision suppor...

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International Symposium on ISKO-Maghreb Concepts and Tools for knowledge Management (ISKO-Maghreb)

作者： Najia Bouha Laboratory Image and Forms Recognition - Intelligent Systems and Communicating IRF -CIS Morocco

The design, engineering and management of urban traffic systems have become increasingly difficult and costly because existing configurations are multiple and complex. Our goal in this article is to present a state of the art modeling techniques, namely the macroscopic model, mesoscopic and microscopic. And we see that in order to solve problems related to space and time encountered in the above models, a new scale model called hybrid appeared. The latter aims to take advantage of conventional models, by adopting the scale model of the phenomenon. The main objective of the system is to improve urban traffic flow and optimize the flow through operating rules and management. However, the problems related to the design of control systems is the control of the spatial and temporal consistency of decisions, given the characteristics of controlled systems and their environment. The second part of this article will be devoted to the study of some tools to help the existing decision. On the other hand, the approach based on agents used to design models of non-centralized control and self-organized and to improve system responsiveness decision. Un agent is a hardware or software that supports context autonomous decision-making The last part of this article discusses these concepts and the concepts of multi-agent approach.

关键词： Vehicles Microscopy Computational modeling Roads Adaptation models Vehicle dynamics Control systems

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Gait Planning and Motion Control Based on Vrep Simulation for Quadruped Robot 5

Gait Planning and Motion Control Based on Vrep Simulation fo...

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5th World Robot Conference Symposium on Advanced Robotics and Automation, WRC SARA 2023

作者： Zhou, Linqi Chen, Zhihua Liu, Jun Liu, Zhi Chen, Yumeng Zhang, Liting Nanchang Hangkong University Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition Moe Key Lab of Nondestructive Testing Technology Nanchang330063 China Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing100081 China

ISBN: (纸本)9798350307320

Gait planning of quadruped robots plays an important role in achieving less walking, including dynamic and static gait. In this article, a static and dynamic gait control method based on center of gravity stability margin is proposed. Firstly, the robot model and kinematics modeling are introduced. Secondly, the robot's foot static and dynamic gait were planned and the foot trajectory was designed. Finally, two types of gait of the robot were simulated using Vrep simulation software, and the differences in stability and speed between the coordinated gait with speed and stability in the static and dynamic gait of a 12 degree of freedom robot were analyzed, verifying the effectiveness of the gait control method proposed in this paper. © 2023 IEEE.

关键词： Robot programming

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Modeling and simulation of multi-agent systems: Principle influence / reaction

Modeling and simulation of multi-agent systems: Principle in...

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Colloquium in Information Science and Technology (CIST)

作者： Najia Bouha Laboratory Image and Forms Recognition - Intelligent Systems and Communicating IRF - SIC - university Ibnou Zohr - Agadir - Morocco Laboratory of Computer Engineering and Automatic of Artois LGI2A - university Artois 62400 - Béthune - France

This paper presents a state of the art modeling techniques, namely the macroscopic model, mesoscopic and microscopic. And we will see that in order to solve problems related to space and time encountered in the above models, a new scale model called hybrid appeared Its purpose is to take advantage of conventional models, by adopting the model of the phenomenon. The simulation of multi-agent systems based on the direct representation of behaviors, actions and interactions of a set of autonomous entities operating in a common environment. In this context, the global dynamics of a system at the macroscopic level is seen as the result of the outcome of dynamic interactions that take place at the microscopic level. One of the problems associated with this approach is the link between these two levels of modeling, which is fundamental. However, deduct the macroscopic dynamics of a system based on the dynamics of microscopic level raises many technical and conceptual problems. The model Influence / Reaction of Ferber and Müller will be discussed in detail in this article we will emphasize its shortcomings, and present later the IRM4S (An Influence Reaction Model for Simulation) model that clearly explains the principleand which allows to articulate modeling micro level with the macro-level.

关键词： Decision support systems Computational modeling Microscopy Multi-agent systems Analytical models Extraterrestrial phenomena Context

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Parameter estimation of photovoltaic modules using analytical and numerical/iterative approaches: A comparative study

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Materials Today: Proceedings 2022年 52卷 1-6页

作者： Souad Lidaighbi Mustapha Elyaqouti Khalid Assalaou Dris Ben Hmamou Driss Saadaoui Jihad H'roura Materials and Renewable Energy Laboratory Agadir Faculty of Sciences Ibn Zohr University BP 8106 80000 Agadir Morocco Laboratory of Electronics Signal Processing and Physical Modeling Faculty of Sciences of Agadir Ibn Zohr University BP 8106 80000 Agadir Morocco Laboratory of Images and Pattern Recognition - Intelligent and Communicating Systems Faculty of Sciences of Agadir Ibn Zohr University BP 8106 80000 Agadir Morocco

Modeling photovoltaic (PV) modules is fundamental for analyzing their efficiency and performance under different operating conditions. Generally, photovoltaic module modeling is based on a suitable equivalent circuit and a set of parameters representing the PV module's properties. Defining these parameters is not a trivial task, as they are usually not included in the technical documentation of the module. Therefore, the need to find suitable values for the model parameters becomes imperative. In this paper, we will test and compare two methods of extracting single-diode model (SDM) parameters: analytical and numerical, under standard test conditions (STC conditions). We examined the performance of six techniques: three analytical and three numerical. Except for Saleem technique, which tends to underestimate the I-V and P-V curves in the MPP zone, the results demonstrated that both approaches (analytical and iterative/numerical) are valid and accurate for predicting the I-V and P-V curves under STC conditions.

关键词： Photovoltaic module Single-diode model Parameters extraction Analytical methods Numerical methods

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Gait Planning and Motion Control Based on Vrep Simulation for Quadruped Robot

Gait Planning and Motion Control Based on Vrep Simulation fo...

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WRC Symposium on Advanced Robotics and Automation (WRC SARA)

作者： Linqi Zhou Zhihua Chen Jun Liu Zhi Liu Yumeng Chen Liting Zhang key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition and MOE Key Lab of Nondestructive Testing Technology Nanchang Hangkong University Nanchang China State Key Laboratory of Intelligent Control and Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing China

Gait planning of quadruped robots plays an important role in achieving less walking, including dynamic and static gait. In this article, a static and dynamic gait control method based on center of gravity stability margin is proposed. Firstly, the robot model and kinematics modeling are introduced. Secondly, the robot’s foot static and dynamic gait were planned and the foot trajectory was designed. Finally, two types of gait of the robot were simulated using Vrep simulation software, and the differences in stability and speed between the coordinated gait with speed and stability in the static and dynamic gait of a 12 degree of freedom robot were analyzed, verifying the effectiveness of the gait control method proposed in this paper.

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An Active Landing Recovery Method for Quadrotor UAV: Localization, Tracking and Buffering Landing

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IFAC-PapersOnLine 2023年第2期56卷 3366-3372页

作者： Yongkang Xu Zhihua Chen Shoukun Wang Junzheng Wang National Key Lab of Autonomous Intelligent Unmanned Systems Beijing Institute of Technology Beijing CO 100081 P.R.China Key Laboratory of Jiangxi Province for Image Processing and Pattern Recognition and MOE Key Lab of Nondestructive Testing Technology School of Information Engineering Nanchang Hangkong University Nanchang CO 330063 P.R. China

This paper proposes a principle of fully autonomous ground mobile landing recovery of Unmanned Aerial Vehicles (UAV) for the problems of relatively fixed landing point, passive recovery, poor flexibility, and environmental adaptability, which mainly includes localization, landing point tracking, and buffering landing for quadrotor UAV. Firstly, aiming at the problem that it is difficult to accurately obtain the position of a UAV in dynamic mobile landing recovery, a target location method based on Asynchronous Multisensor Information Fusion(AMIF) and servo turntable focus tracking is proposed. Secondly, to achieve fast and high-precision tracking of UAVs, a tracking control strategy of an independently driven landing recovery system and a Stewart six-degree of freedom platform is proposed. Then, to solve the problems of large impact force and center of gravity instability in the landing process of UAV, a stationarity control algorithm based on model prediction and a compliance control algorithm based on adaptive variable impedance are designed to achieve active compliance control while adjusting the position and attitude of the receiving surface in real-time. Finally, a quadrotor unmanned landing and recovery experimental platform is built to verify the feasibility of the ground mobile landing and recovery strategy proposed in this paper and the effectiveness of the control algorithm.

关键词： Quadrotor UAV Mobile Autonomous recovery Target localization Falling point tracking Buffering landing

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Hybrid Data-Free Knowledge Distillation

arXiv

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arXiv 2024年

作者： Tang, Jialiang Chen, Shuo Gong, Chen School of Computer Science and Engineering Nanjing University of Science and Technology China Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information of Ministry of Education China Jiangsu Key Laboratory of Image and Video Understanding for Social Security China Center for Advanced Intelligence Project RIKEN Japan Department of Automation Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University China

Data-free knowledge distillation aims to learn a compact student network from a pre-trained large teacher network without using the original training data of the teacher network. Existing collection-based and generation-based methods train student networks by collecting massive real examples and generating synthetic examples, respectively. However, they inevitably become weak in practical scenarios due to the difficulties in gathering or emulating sufficient real-world data. To solve this problem, we propose a novel method called Hybrid Data-Free Distillation (HiDFD), which leverages only a small amount of collected data as well as generates sufficient examples for training student networks. Our HiDFD comprises two primary modules, i.e., the teacher-guided generation and student distillation. The teacher-guided generation module guides a Generative Adversarial Network (GAN) by the teacher network to produce high-quality synthetic examples from very few real-world collected examples. Specifically, we design a feature integration mechanism to prevent the GAN from overfitting and facilitate the reliable representation learning from the teacher network. Meanwhile, we drive a category frequency smoothing technique via the teacher network to balance the generative training of each category. In the student distillation module, we explore a data inflation strategy to properly utilize a blend of real and synthetic data to train the student network via a classifier-sharing-based feature alignment technique. Intensive experiments across multiple benchmarks demonstrate that our HiDFD can achieve state-of-the-art performance using 120 times less collected data than existing methods. Code is available at https://***/tangjialiang97/HiDFD. Copyright © 2024, The Authors. All rights reserved.

关键词： Students

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Learning data-adaptive nonparametric kernels

arXiv

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arXiv 2018年

作者： Liu, Fanghui Huang, Xiaolin Gong, Chen Yang, Jie Li, Li Institute of Image Processing and Pattern Recognition Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of Intelligent Perception and Systems for High-Dimensional Information Ministry of Education School of Computer Science and Engineering Nanjing University of Science and Technology Nanjing210094 China Department of Automation Tsinghua University

Kernel methods have been extensively used in a variety of machine learning tasks such as classification, clustering, and dimensionality reduction. For complicated practical tasks, the traditional kernels, e.g., Gaussian kernel and sigmoid kernel, or their combinations are often not sufficiently flexible to fit the data. In this paper, we present a Data-Adaptive Nonparametric Kernel (DANK) learning framework in a data-driven manner. To be specific, in model formulation, we impose an adaptive matrix on the kernel/Gram matrix in an entry-wise strategy. Since we do not specify the formulation of the adaptive matrix, each entry in the adaptive matrix can be directly and flexibly learned from the data. Therefore, the solution space of the learned kernel is largely expanded, which makes our DANK model flexible to capture the data with different local statistical properties. Specifically, the proposed kernel learning framework can be seamlessly embedded to support vector machines (SVM) and support vector regression (SVR), which has the capability of enlarging the margin between classes and reducing the model generalization error. Theoretically, we demonstrate that the objective function of our DANK model embedded in SVM/SVR is gradient-Lipschitz continuous. Thereby, the training process for kernel and parameter learning in SVM/SVR can be efficiently optimized in a unified framework. Further, to address the scalability issue in nonparametric kernel learning framework, we decompose the entire optimization problem in DANK into several smaller easy-to-solve problems, so that our DANK model can be efficiently approximated by this partition. The effectiveness of this approximation is demonstrated by both empirical studies and theoretical guarantees. Experimentally, the proposed DANK model embedded in SVM/SVR achieves encouraging performance on various classification and regression benchmark datasets when compared with other representative kernel learning based algorithms. Copyrig

关键词： Matrix algebra

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