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2024 16th International Conference on Graphics and Image Processing, ICGIP 2024

作者： Sun, Liliang He, Yuanlie Li, Wensheng Feng, Fujian Liang, Yihui School of Computer Guangdong University of Technology Guangzhou510000 China School of Computer Science Zhongshan Institute University of Electronic Science and Technology of China Zhongshan528400 China Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guizhou Minzu University Guiyang550025 China

ISBN: (数字)9781510688780

ISBN: (纸本)9781510688773

This paper focuses on the image composition of transparent objects, where existing image matting methods suffer from composition errors due to the lack of accurate foreground during the composition process. We propose a foreground prediction model named ALGM, which leverages the local feature extraction capabilities of Convolutional Neural Networks (CNNs) and incorporates an attention mechanism for global information modeling. The proposed alpha-assisted foreground prediction module extracts foreground information from the original image and conveys it. The extracted foreground color information is combined with the deep structural features of the encoder and used for foreground color prediction. ALGM reduces image composition errors in the quantitative data from the Composition-1k dataset and improves the visual quality of composed images on the AIM-500 and Transparent-460 datasets. © 2025 SPIE.

关键词： Prediction models

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Fire Detection Based on Flame Enhancement for Weak Fires 19th

Fire Detection Based on Flame Enhancement for Weak Fires

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19th Chinese Conference on Image and Graphics Technologies and Applications, IGTA 2024

作者： Chen, Kuan Wen, Wen Feng, Fujian Xu, Xiang Liang, Yihui School of Computer Guangdong University of Technology Guangzhou510000 China School of Computer Science Zhongshan Institute University of Electronic Science and Technology of China Zhongshan528400 China Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guizhou Minzu University Guiyang550025 China

ISBN: (纸本)9789819799183

Detecting weak fire, such as overexposed and highly transparent flames, remains a significant challenge in vision-based fire detection. Convolutional Neural Network (CNN) based methods are widely used for automatic fire feature extraction, but they struggle to accurately recognize overexposed flames similar to the background and highly transparent flames that blend with the background, leading to false negative fire detection results. To address this issue, we have established a large-scale fire detection dataset with weak flames and introduce a fire detection method based on flame context enhancement. While employing a flame feature extraction module to identify and delineate the potential flame area, the proposed method primarily introduces a flame context module to capture the effective features of weak flames from this area, significantly enhancing the understanding of fires. Experimental results show that the proposed method can effectively reduce false negatives and improves the recall rate for detecting weak flames. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Premixed flames

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Adaptive Pixel Pair Generation Strategy for Image Matting Methods Based on Pixel Pair Optimization 19th

Adaptive Pixel Pair Generation Strategy for Image Matting Me...

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19th Chinese Conference on Image and Graphics Technologies and Applications, IGTA 2024

作者： Zheng, Jiamin Wen, Wen Liang, Yihui Feng, Fujian Xu, Xiang School of Computer Guangdong University of Technology Guangzhou510000 China School of Computer Science Zhongshan Institute University of Electronic Science and Technology of China Zhongshan528400 China Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guizhou Minzu University Guiyang550025 China

ISBN: (纸本)9789819799183

Natural image matting plays a crucial role in numerous real-world applications. Image matting methods based on pixel pair optimization is a type of matting algorithm, which has significant advantages in parallel computation, handling images with similar foreground and background, and operating under limited computing time. However, these methods cannot provide high-quality alpha mattes for high-resolution images within limited computational resources. In this paper, we design an adaptive pixel pair generation strategy to solve the above problem. This strategy adaptively generates pixel pair for the unknown pixel according to its estimated alpha value, which promotes diversity of pixel pair and improves the efficiency of pixel pair optimization. It categorizes unknown pixels into three types and additionally incorporates nearby foreground and background pixels to generate pixel pair. Experimental results show that using our strategy can achieve high-quality alpha mattes and competitive matting performance under limited computational resources. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.

关键词： Pixels

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Efficient Image Super-Resolution With Feature Interaction Weighted Hybrid Network

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IEEE Transactions on Multimedia 2025年 27卷 2256-2267页

作者： Li, Wenjie Li, Juncheng Gao, Guangwei Deng, Weihong Yang, Jian Qi, Guo-Jun Lin, Chia-Wen Beijing University of Posts and Telecommunications Pattern Recognition and Intelligent System Laboratory School of Artificial Intelligence Beijing100080 China Shanghai University School of Communication and Information Engineering Shanghai200444 China Nanjing University of Posts and Telecommunications IVIPLab Institute of Advanced Technology Nanjing210046 China Ministry of Education Key Laboratory of Artificial Intelligence Shanghai200240 China Soochow University Provincial Key Laboratory for Computer Information Processing Technology Suzhou215006 China Nanjing University of Science and Technology School of Computer Science and Technology Nanjing210094 China Westlake University Research Center for Industries of the Future School of Engineering Hangzhou310024 China OPPO Research SeattleWA98101 United States National Tsing Hua University Department of Electrical Engineering Institute of Communications Engneering Hsinchu300044 Taiwan

Lightweight image super-resolution aims to reconstruct high-resolution images from low-resolution images using low computational costs. However, existing methods result in the loss of middle-layer features due to activation functions. To minimize the impact of intermediate feature loss on reconstruction quality, we propose a Feature Interaction Weighted Hybrid Network (FIWHN), which comprises a series of Wide-residual Distillation Interaction Block (WDIB) as the backbone. Every third WDIB forms a Feature Shuffle Weighted Group (FSWG) by applying mutual information shuffle and fusion. Moreover, to mitigate the negative effects of intermediate feature loss, we introduce Wide Residual Weighting units within WDIB. These units effectively fuse features of varying levels of detail through a Wide-residual Distillation Connection (WRDC) and a Self-Calibrating Fusion (SCF). To compensate for global feature deficiencies, we incorporate a Transformer and explore a novel architecture to combine CNN and Transformer. We show that our FIWHN achieves a favorable balance between performance and efficiency through extensive experiments on low-level and high-level tasks. © 1999-2012 IEEE.

关键词： Transformers Convolutional neural networks Computational modeling Feature extraction Training Superresolution Adaptation models Computer architecture Telecommunications Image reconstruction

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Adaptive geodesic feedback controller design for the quadrotor

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International Journal of Vehicle Autonomous systems 2020年第3-4期15卷 319-342页

作者： Liu, Chao Yang, Shengyi Key Laboratory of Pattern Recognition and Intelligent System Guizhou Minzu University Huaxi District Guizhou Province Guiyang China

In this paper, a non-linear adaptive control method based on SO(3) for the quadrotor attitude tracking is proposed. Distinct from other control methods on Euclidean space, the controller proposed is developed on SO(3), which can avoid singularities and ambiguities. Besides, the geodesic on SO(3) is used to provide the shortest curve between the current attitude configuration and the desire attitude configuration. Then, a feedback controller based on geodesic is derived. To solve the problem that the inertial tensor of the quadrotor is unknown, an adaptive term is designed with the Lyapunov theory to estimate the inertial tensor. Thus, the almost global asymptotic stability of the quadrotor attitude tracking is achieved without the prior knowledge of the quadrotor inertia tensor. The numerical simulations are utilised to show better control performance of the adaptive geodesic feedback control method. Copyright © 2020 Inderscience Enterprises Ltd.

关键词： Controllers

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Geometric Numerical Integral Method in Compact Lie Group 6

Geometric Numerical Integral Method in Compact Lie Group

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6th IEEE International Conference on intelligent Computing and Signal Processing, ICSP 2021

作者： Liu, Chao Yang, Shengyi Guizhou Minzu University Key Laboratory of Pattern Recognition Intelligent System of Guizhou Province Gui Yang China

ISBN: (纸本)9780738143705

Three dimensions special orthogonal group SO (3) is widely used to describe the rotation kinematics of the rigid body without local coordinates, which can avoid rotation singularity and unwinding in traditional methods. Propagating the rotation kinematics in SO (3) with a specific geometric integration method is not only to obtained numerical results with improved qualitative behavior, but also provided more accurate long-time integration results. While many studies have focused on geometric integration algorithms to preserve the geometric structure, this work has the additional objective of studying result accuracy. Integral curves on SO (3) obtained using the third-order Crouch-Grossman Lie group method are compared with numerical results using the third-order RKMK algorithms, the exponential coordinates method, and the simple projection method. Results show that the use of the Crouch-Grossman Lie group method better preserves the geometric structure of SO (3) for the larger time steps considered. It is also found that the third-order Crouch-Grossman algorithm is more accurate than the RKMK except for the smallest time step used. © 2021 IEEE.

关键词： Geometry

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Research on Teaching Reform of 'Motor and Drive'Based on Matlab Simulation 2

Research on Teaching Reform of 'Motor and Drive'Based on Mat...

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2nd International Conference on Education, Knowledge and Information Management, ICEKIM 2021

作者： Chengwei, Zhang Yihua, Liang Liu, Chao Yang, Shengyi Key Laboratory of Pattern Recognition and Intelligent System of Guizhou Province Guizhou Minzu University Gui Yang China

ISBN: (纸本)9781728168340

'Motor and Drive' is a professional basic course with strong theory and wide application in practical engineering. Its theory is abstract and formula is complex, which is considered by teachers and automation students as one of the professional courses difficult to teach and learn. In order to better teaching and learning, teaching reform is provided. The teaching content is optimized, the teaching methods, experimental methods and assessment methods are reformed based on matlab simulation. It is helpful to improve the teaching quality, stimulate students' learning enthusiasm and solve practical problems. The teaching reform foundation of 'motor and drive' is provided in this paper. © 2021 IEEE.

关键词： Teaching

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An image matching evolutionary algorithm based on Hu invariant moments

An image matching evolutionary algorithm based on Hu invaria...

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3rd International Conference on Image Analysis and Signal Processing, IASP 2011

作者： Zhang, Ruliang Wang, Lin Key Laboratory of Pattern Recognition and Intelligent Control Guizhou University for Nationalities Guiyang China

ISBN: (纸本)9781612848808

This paper presents an image matching evolutionary algorithm (called IMEA algorithm) based on Hu invariant moments. First, the population is initialized. A group of searched subgraphs is constructed. Second, the fitness function based on Hu invariant moments is designed. The seven Hu invariant moments of the template image and the searched subgraph are calculated. The Euclidean distance of Hu invariant moments is used to measure similarity between the template image and the searched subgraph. The template image and the searched subgraph are matched if these Euclidean distances are less than the set threshold. Finally, a new searched subgraph is constructed by means of a new evolutionary strategy. The new searched subgraph replaces the searched subgraph whose value of the fitness function is maximum. Experimental results demonstrate the great robustness and efficiency of the IMEA algorithm. © 2011 IEEE.

关键词： Evolutionary algorithms

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Feature Decoupled of Deep Mutual Information Maximization 2

Feature Decoupled of Deep Mutual Information Maximization

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2nd International Conference on Automation, Robotics and Computer Engineering, ICARCE 2023

作者： He, Xing Peng, Changgen Wang, Lin Tan, Weijie Wang, Zifan State Key Laboratory of Public Big Data College of Computer Science and Technology Guizhou University Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guizhou Minzu University Guiyang China Guizhou Big Data Academy Guizhou University Guiyang China Guizhou Minzu University Guizhou Key Laboratory of Pattern Recognition and Intelligent System Guiyang China Institute of Guizhou Aerospace Measuring and Testing Technology Guiyang China

ISBN: (纸本)9798350308341

In deep learning, supervised learning techniques usually require a large amount of expensive labeled data to train the network, and the feature representations extracted by the model usually mix multiple attributes, resulting in feature representations that are difficult to decouple and are non-interpretable, which restricts the application and development of deep learning techniques, and for this reason, it is particularly important to study decoupled feature representation methods for unsupervised learning. Although the Learning deep representations by mutual information estimation and maximization (DIM) method achieves excellent results in unsupervised learning, the feature representations learned by the DIM method still suffer from the problem of difficult decoupling. decoupling problem. To address this problem, we minimize the mutual information between the intermediate layer feature representations learned by the hidden layer of the encoder during the encoder training process, so that the features learned by each filter are as uncorrelated as possible, thus realizing feature decoupling, and our method is called FP-DIM. Finally, the effectiveness of the FP-DIM method is verified on the CIFAR-10, STL-10, and Fashion-MNIST datasets. The experiments show that our proposed FP-DIM method is more significant for the learned decouplable middle layer feature representation. Finally, we also propose a reflection of future research for the FP-DIM method, aiming to provide a research idea and direction for solving unsupervised interpretable machine learning and to lay a solid theoretical and application foundation for machine learning fields such as image classification and migration learning. © 2023 IEEE.

关键词： Unsupervised learning

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Size and Defect Detection of Valve Based on Computer Vision

Size and Defect Detection of Valve Based on Computer Vision

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2022 International Conference on Computer Graphics, Artificial Intelligence, and Data Processing, ICCAID 2022

作者： Yan, Xiaobo Feng, Le Tan, Mian Yang, Yuan Zhang, Yu Wang, Lin Guizhou Key Laboratory of Pattern Recognition and Intelligent System China Guizhou Minzu University Guiyang550025 China Guiyang Fusheng Intelligent Technology Co. Ltd China

ISBN: (纸本)9781510663350

Engine valve is the core component of the engine, and its quality determines the performance of the engine. In industrial production quality inspection, it is necessary to detect the size of the valve and whether there are defects on the surface. Usually, the quality of the valve is determined by comparing the image of the valve surface with the standard image. However, the existing surface defect detection technology cannot detect the curved surface device. In order to solve this problem, this paper designs a valve size and defect detection method based on computer vision. The experimental results show that the method can quickly and accurately detect the rod diameter, groove radius and surface defects of the valve. The method is practical, robust and real-time. © 2023 SPIE.

关键词： Computer vision

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