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MIPPR 2007: Automatic Target Recognition and image Analysis;and Multispectral image Acquisition

作者： Geng, Hui Hong, Hanyu Zhang, Yan Lin, Zhimin Lab. for Image Processing and Intelligence Control Wuhan Institute of Technology Hubei 430074 China

ISBN: (纸本)9780819469502

COG (chip on glass) bonding is widely used in LCD industry. The alignment of marks in COG bonding needs high precision and reliability. It is of utmost importance to find two marks in COG fast and exactly. Its key technique is to use the advanced optical system to get the two-marked positions of chip on the glass, and to use the PLC procedure control to complete the automatic alignment. A series of experiments are performed to test the algorithms proposed, which show that the fast alignment of marks in COG bonding based on multi-resolution is both rational and highly effective.

关键词： Liquid crystal displays

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The depth information estimation of microscope defocus image based-on Markov random field

The depth information estimation of microscope defocus image...

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2008 IEEE International Conference on Robotics, Automation and Mechatronics, RAM 2008

作者： Zeng, Xiangjin Huang, Xinhan Wang, Min Peng Li Department of Control Science and Engineering Key Lab. of Image Processing and Intelligence Control HUST Wuhan China

ISBN: (纸本)9781424416769

For depth information estimation of microscope defocus image, a blur parameter model of defocus image based on Markov random field has been present. It converts problem of depth estimation into optimization problem. An improved Iterated Conditional Modes Algorithm has been applied to complete optimization problem, which the select of initial point employed Least squares estimate algorithm prevents that the result gets into local optimization. The experiments and simulations prove that the model and algorithm is efficiency. © 2008 IEEE.

关键词： Microscopes

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MP-MAT: A 3D-AND-INSTANCE-AWARE HUMAN MATTING AND EDITING FRAMEWORK WITH MULTIPLANE REPRESENTATION

arXiv

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arXiv 2025年

作者： Jiao, Siyi Zeng, Wenzheng Li, Yerong Zhang, Huayu Gao, Changxin Sang, Nong Shou, Mike Zheng Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology China Show Lab National University of Singapore Singapore

Human instance matting aims to estimate an alpha matte for each human instance in an image, which is challenging as it easily fails in complex cases requiring disentangling mingled pixels belonging to multiple instances along hairy and thin boundary structures. In this work, we address this by introducing MP-Mat, a novel 3D-and-instance-aware matting framework with multiplane representation, where the multiplane concept is designed from two different perspectives: scene geometry level and instance level. Specifically, we first build feature-level multiplane representations to split the scene into multiple planes based on depth differences. This approach makes the scene representation 3D-aware, and can serve as an effective clue for splitting instances in different 3D positions, thereby improving interpretability and boundary handling ability especially in occlusion areas. Then, we introduce another multiplane representation that splits the scene in an instance-level perspective, and represents each instance with both matte and color. We also treat background as a special instance, which is often overlooked by existing methods. Such an instance-level representation facilitates both foreground and background content awareness, and is useful for other down-stream tasks like image editing. Once built, the representation can be reused to realize controllab.e instance-level image editing with high efficiency. Extensive experiments validate the clear advantage of MP-Mat in matting task. We also demonstrate its superiority in image editing tasks, an area under-explored by existing matting-focused methods, where our approach under zero-shot inference even outperforms trained specialized image editing techniques by large margins. Code is open-sourced at https://***/JiaoSiyi/***. Copyright © 2025, The Authors. All rights reserved.

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3-D reconstruction of blood vessels skeleton based on Neural network

3-D reconstruction of blood vessels skeleton based on Neural...

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13th International Conference on Neural Information processing, ICONIP 2006

作者： Zhiguo, Cao Bo, Peng Institute of Image Processing and Artificial Intelligence Huazhong University of Sci. and Tec. State Key Lab. for Image Processing and Intelligent Control Wuhan 430074 Hubei China

ISBN: (纸本)3540464840

For the 3-D reconstruction of blood vessels skeleton from biplane angiography system, an efficient 3-D reconstruction method based on neural network(NN) is proposed in this paper. First, we find a set of 2-D corresponding points on the vessels' skeleton in the matched image pair. Secondly, NN is utilized to build the relationships between the 3-D points and their projective 2-D points. Thirdly, by feeding the corresponding points we found into the NN, the 3D coordinates of the points on vessels can be obtained. At last we employ B-spline interpolation to improve reconstruction performance. Experiment results demonstrate the efficiency of the new method. © Springer-Verlag Berlin Heidelberg 2006.

关键词： Blood vessels

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Prompt-guided consistency learning for multi-lab.l classification with incomplete lab.ls

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Neural Networks 2025年

作者： Shouwen Wang Qian Wan Zihan Zhang Zhigang Zeng School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan 430074 China Key Lab of Image Processing and Intelligent Control Ministry of Education Wuhan 430074 China Independent Researcher Wuhan 430074 China

Addressing insufficient supervision and improving model generalization are essential for multi-lab.l classification with incomplete annotations, i.e. , partial and single positive lab.ls. Recent studies incorporate pseudo-lab.ls to provide additional supervision and enhance model generalization. However, the noise in pseudo-lab.ls generated by the model tends to accumulate, resulting in confirmation bias during training. Self-correction methods, commonly used approaches for mitigating confirmation bias, rely on model predictions but remain susceptible to confirmation bias caused by visual confusion, including both visual ambiguity and similarity. To reduce visual confusion, we propose a prompt-guided consistency learning (PGCL) framework designed for two incomplete lab.ling settings. Specifically, we introduce an intra-category supervised contrastive loss, which imposes consistency constraints on reliable positive class samples in the feature space of each category, rather than across the feature space of all categories, as in traditional inter-category supervised contrastive loss. Building on this, the distinction between true positive and visual confusion samples for each category is enhanced through lab.l-level contrasting of the same category. Additionally, we develop a class-specific semantic decoupling module that leverages CLIP’s strong vision-language alignment capability, since the proposed contrastive loss requires high-quality lab.l-level representations as contrastive samples. Extensive experimental results on multiple datasets demonstrate that our method can effectively address the problems of two incomplete lab.ling settings and achieve state-of-the-art performance.

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A comparative study of radial basis function neural networks in dynamic clustering algorithm

A comparative study of radial basis function neural networks...

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MIPPR 2009 - Pattern Recognition and Computer Vision: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Zhou, Peng Li, Dehua Wu, Hong Zeng, Jun Chen, Feng State Key Lab. for Image Processing and Intelligent Control Institute for Pattern Recognition and Intelligence Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478078

This paper developed two learning procedure, respectively, based on the orthogonal least squares (OLS) method and the "Innovation- Contribution" criterion (ICc) proposed newly. The orthogonal use of the stepwise-regression algorithm of the ICc mages the model structure independent of the selected term sequence and reduces the cluster region further as compared with orthogonal least squares (OLS). as the Bayesian information criteria (BIC) method is incorporate into the clustering process of the ICc, except for the widths of Gaussian functions, it has no other parameter that need tuning ,but the user is required to specify the tolerance ρ, which is relevant to noises and will be difficult to implement in the real system, for the OLS algorithm. The two algorithms are employed to the Radial Basis Function Neural Networks (RBFNN) to compare its performance for different noise nonlinear dynamic systems. Experimental results show that they provide an efficient approximation to the required results for fitting models, but the clustering procedures of the ICc is substantially better solutions than does the OLS. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Radial basis function networks

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Underwater Perception and Autonomous Operation for Underwater Vehicle-Manipulator Systems: Methodology and Experiment

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IEEE/ASME Transactions on Mechatronics 2025年

作者： Jiang, Chaicheng Xiong, Xinyang Xiang, Xianbo Zeng, Zhigang Zhang, Fumin Huazhong University of Science and Technology School of Artificial Intelligence and Automation Wuhan 430074 China Huazhong University of Science and Technology School of Naval Architecture and Ocean Engineering Wuhan 430074 China Huazhong University of Science and Technology School of Naval Architecture and Ocean Engineering School of Artificial Intelligence and Automation State Key Lab of Intelligent Manufacturing Equipment and Technology Wuhan 430074 China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control The Education Ministry of China Wuhan 430074 China Hong Kong University of Science and Technology Department of Electronic and Computer Engineering Clear Water Bay Hong Kong Hong Kong

Camera-equipped underwater vehicle-manipulator systems (UVMS) can achieve autonomous underwater operations through visual servoing. However, current methods excessively rely on auxiliary means for target's visual information and do not sufficiently consider the target's pose when designing visual servoing schemes. As a result, UVMS can only perform dynamic positioning or grasp simple-shaped targets like sea urchins. In this article, we are devoted to making the UVMS autonomously complete more complex underwater operations, such as valve switching and pipe handling. First, an underwater target perception system is proposed to address the issue of discontinuous target position estimation caused by various interferences. Second, a deep neural network-based grasping mechanism controller is proposed to enable the manipulator to grasp targets in various initial poses using the target image. Third, a decoupled visual servoing scheme is proposed for the motion control of the UVMS, and in collab.ration with a designed task supervisor to ensure that the UVMS can complete the underwater operation autonomously. To validate the effectiveness of the proposed methods, underwater experiments are conducted based on a UVMS prototype. The UVMS succeeds to autonomously switch different types of valves and handle the pipe. Experiments conducted under dynamic currents validated the reliability and robustness of the proposed methods. © 1996-2012 IEEE.

关键词： Autonomous underwater operations deep neural network underwater vehicle-manipulator systems (UVMS) visual perception visual servoing

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Integer Haar wavelet for romote sensing image compression 6

Integer Haar wavelet for romote sensing image compression

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6th International Conference on Signal processing, ICSP 2002

作者： Zhenhua, Wang Hongbo, Xu Yan, Tian Jinwen, Tian Jian, Liu State Key Lab. for Image Processing and Intelligent Control Institute for Pattern Recognition and Artificial Intelligence Huazhong University of Science and Technology Wuhan430074 China

ISBN: (纸本)0780374886

With the development of remote sensing technique, onboard data compression has become an urgent need and a lot of study has been directed toward the development of efficient techniques. In this paper, the construction approach of integer Haar is discussed briefly, and a'simple image compression scheme based on integer Haar Wavelet Transform and block DPCM is proposed. The scheme can be easily designed for data processing in real-time system of remote sensing with parellel algorithm. Simulation experimental results demonstrate that the proposed approach is a efficient image compression method. © 2002 IEEE.

关键词： image compression

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Modeling of cortical signals using echo state networks

Modeling of cortical signals using echo state networks

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MIPPR 2009 - Pattern Recognition and Computer Vision: 6th International Symposium on Multispectral image processing and Pattern Recognition

作者： Zhou, Hanying Wang, Yongji Huang, Jiangshuai Key Lab. for Image Processing and Intelligent Control Department of Control Science and Engineering Huazhong University of Science and Technology China

ISBN: (纸本)9780819478078

Diverse modeling frameworks have been utilized with the ultimate goal of translating brain cortical signals into prediction of visible behavior. The inputs to these models are usually multidimensional neural recordings collected from relevant regions of a monkey's brain while the outputs are the associated behavior which is typically the 2-D or 3-D hand position of a primate. Here our task is to set up a proper model in order to figure out the move trajectories by input the neural signals which are simultaneously collected in the experiment. In this paper, we propose to use Echo State Networks (ESN) to map the neural firing activities into hand positions. ESN is a newly developed recurrent neural network(RNN) model. Besides its dynamic property and short term memory just as other recurrent neural networks have, it has a special echo state property which endows it with the ability to model nonlinear dynamic systems powerfully. What distinguished it from transitional recurrent neural networks most significantly is its special learning method. In this paper we train this net with a refined version of its typical training method and get a better model. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Brain

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Design of a wearable rehabilitation robotic hand actuated by pneumatic artificial muscles

Design of a wearable rehabilitation robotic hand actuated by...

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2009 7th Asian control Conference, ASCC 2009

作者： Kexin, Xing Jian, Huang Qi, Xu Yongji, Wang Key Lab. of Image Processing and Intelligent Control Department of Control Science and Technology Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9788995605691

Intensive task-oriented repetitive physical therapies provided by individualized interaction between the patient and the rehabilitation specialist can improve the hand motor performance of the patient survived from stroke or traumatic brain injury. However, the therapy is time-consuming and expensive. Furthermore, it is difficult to evaluate the result of therapy quantitatively and objectively. The goal of this research is to develop a novel wearable device for robotic assistive hand repetitive therapy. We designed a pneumatic artificial muscle (PAM) driven rehabilitation robotic hand that is wearable and provides assistive forces required for grasping and release movements. The robot has two distinct degrees of freedom at the thumb and the fingers. The embedded sensors are employed to obtain the feedback position and force information for robot control and quantitative evaluation of task performance. To encourage the patients' self-regulation and improve the performance of the task, a PC based Virtual Reality game was developed. In order to realize a compliant and smooth motion, cubic spline functions are adopted in the trajectory planning of metacarpophalangeal joints. To realize the trajectory tracking control, a conventional PID controller was implemented and evaluated. Experiments were performed to confirm the effectiveness of the proposed device and methods. The robot has the potential of providing supplemental at-home therapy in addition to in the clinic treatment. ©2009 ACA.

关键词： Degrees of freedom (mechanics)

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