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4th international conference on computer graphics and digital image processing, cgdip 2020

4th International Conference on Computer Graphics and Digita...

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4th international conference on computer graphics and digital image processing, cgdip 2020

the proceedings contain 28 papers. the topics discussed include: a command and control system for air defense forces with augmented reality and multimodal interaction;design and production of digital interactive installation for the cultural theme of the belt and road initiative;a smart attendance system for Imam Abdulrahman Bin Faisal University using facial recognition;optimization and high-performance hardware implementation of multipath interference compensation algorithm;high-voltage cable fault analysis base on x-ray image processing;research on path planning of UAV based on ant colony algorithm with angle factor;usability evaluation for user interface design of application for recommender system to enhance the potential of community-based tourism in Phatthalung, thailand;the technology of moving target detection and tracking based on sequential SAR image;a high precision rotating line detection method for the rotation angle measurement based on machine vision;and an image deblurring method based on improved dark channel prior.

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4th international conference on computer Vision and image processing, CVIP 2019

4th International Conference on Computer Vision and Image Pr...

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4th international conference on computer Vision and image processing, CVIP 2019

ISBN: (纸本)9789811540141

the proceedings contain 82 papers. the special focus in this conference is on computer Vision and image processing. the topics include: A method to generate synthetically warped document image;delaunay triangulation based thinning algorithm for alphabet images;a reduced graph cut approach to interactive object segmentation with flexible user input;A new fuzzy clustering algorithm by incorporating constrained class uncertainty-based entropy for brain MR image segmentation;a novel saliency-based cascaded approach for moving object segmentation;a novel graph theoretic image segmentation technique;automated industrial quality control of pipe stacks using computer vision;extraction and recognition of numerals from machine-printed urdu documents;colour sensitive image segmentation using quaternion Algebra;multimodal query based approach for document image retrieval;transformed directional tri concomitant triplet patterns for image retrieval;encoder decoder based image semantic space creation for clothing items retrieval;feature learning for effective content-based image retrieval;two efficient image bag generators for multi-instance multi-label learning;a comparative study of big mart sales prediction;asymmetric wide tele camera fusion for high fidelity digital zoom;energy based convex set hyperspectral endmember extraction algorithm;fast semantic feature extraction using superpixels for soft segmentation;spatially variant laplacian pyramids for multi-frame exposure fusion;Traffic sign recognition using color and spatial transformer network on GPU embedded development board;unsupervised single-view depth estimation for real time inference;preface;towards ocular recognition through local image descriptors;a novel information theoretic cost measure for filtering based feature selection from hyperspectral images;CNN and RF based classification of brain tumors in MR neurological images.

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Research on Oracle Bone Inscription Segmentation and Recognition Model Based on Deep Learning 4

Research on Oracle Bone Inscription Segmentation and Recogni...

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4th IEEE international conference on Electronic Technology, Communication and Information, ICETCI 2024

作者： Li, Donghao Du, Binfang Shandong University Qingdao China

ISBN: (纸本)9798350361643

In this paper, the automatic segmentation and recognition of oracle bone inscription images are studied. the Oracle bone inscription image segmentation model and Oracle bone inscription text recognition model are established by using computer vision technology and deep learning framework, and the application potential and scientific value of deep learning in the field of complex text image recognition are demonstrated. Firstly, we use a variety of digital image processing methods such as bilateral filtering technology and contrast-limited adaptive histogram equalization technology to optimize the recognition conditions of oracle bone inscription images. Secondly, we use the advanced Yolov8 to build a detection model to improve the text detection accuracy in oracle bone inscription images. the effect of the model was evaluated from different dimensions, such as accuracy rate, recall rate, F1 value, etc., to verify the performance of the model. Finally, we trained a model based on Resnet18 architecture to recognize the single word of the oracle bone inscription original topology image. the recognition results were displayed in the form of statistics and graphics, and the prediction accuracy of each character and the overall performance evaluation of the model were recorded in detail, thus verifying the effectiveness and practicability of the proposed method. © 2024 IEEE.

关键词： image enhancement

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Study on image style transfer for graphic creation using VGG19 and Pix2Pix model 4

Study on image style transfer for graphic creation using VGG...

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4th international conference on computer graphics, image, and Virtualization, ICCGIV 2024

作者： Min, Long Shao, Mingrui Liu, Mengwen Li, Xiaozhou Ma, Dengyue Li, Xuelin Liu, Jingjing Faculty of Light Industry Qilu University of Technology 3501 Daxue Road Jinan250300 China State Key Laboratory of Biobased Material and Green Papermaking Qilu University of Technology Shandong Academy of Sciences 3501 Daxue Road Jinan250300 China Key Laboratory of JiNan Digital Twins and Intelligent Water Conservancy Jinan250013 China School of Art & Design Qilu University of Technology 3501 Daxue Road Jinan250300 China Practice Teaching Center of Art & Design Shandong University of Art & Design Jinan250300 China

ISBN: (纸本)9781510683242

In computer vision field, the style transfer technique is to synthesize the style of one image with the content features of another image to generate a new migrated image, thus creating a unique graphic art image. In this thesis, the image style transfers achieved based on the VGG19 network model and pre-trained Pix2Pix network model separately were investigated by the comparison method, and the COCO dataset was selected as the dataset. the experiments used the peak signal-to-noise ratio (PSNR) and the structural similarity index (SSIM) to evaluate the performance of the style transfer images. It can be found that the PSNR of the migrated image of the VGG19 network model is 12.6776 and the SSIM is 0.2981, while the PSNR of the migrated image of the Pix2Pix network model is 12.9153 and the SSIM is 0.3182. the result indicates that the migrated image generated by the Pix2Pix network model is better than that by the VGG19 with respect to the image quality features. © 2024 SPIE.

关键词： Feature extraction image processing Data modeling

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Accelerating Traditional Object Detection Methods on Sophisticated Embedded Systems 4th

Accelerating Traditional Object Detection Methods on Sophist...

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4th international conference on Intelligent Systems and Pattern Recognition-ISPR

作者： Sehairi, Kamal Bouhafs, Abdelkader Boucherit, Ibtissam Mama Bouwmans, thierry Chouireb, Fatima Ecole Normale Super Laghouat Dept Phys Lab Appl Sci & Didact Laghouat Algeria Univ Amar Telidji Laghouat Dept Elect Telecommun Signals & Syst Lab Laghouat Algeria Univ La Rochelle Dept Comp Sci Lab Math Image & Applicat La Rochelle France

ISBN: (纸本)9783031821523;9783031821530

Identifying and locating objects in images and videos, including elements like traffic signs, vehicles, buildings, and people, constitutes a fundamental and demanding task in computer vision, known as object detection. Due to the higher computing complexity of this technique and the large amount of data carried by the video signal, it is nearly impossible for ordinary general-purpose processors GPPs or CPUs to run these techniques in real-time, especially for embedded systems applications. therefore, special hardware that can acquire, control, or execute in parallel is required. these specialized hardware systems include digital Signal Processors DSPs, Field Programmable Gate Arrays FPGAs, Visual processing Units VPUs, Tensor processing Units TPUs, Neural processing Units NPUs or graphics processing Units GPUs. this work presents the benefits of accelerating traditional object detection methods on a high-end embedded system, the Jetson Nano Developer Kit. this single computer board is equipped with the Tegra K1 System on Chip SoC, which is composed of a quad-core ARM A15 and 192 cores of Kepler-embedded GPU. Computing acceleration was ensured via the use of the CUDA OpenCV library for both the Histogram of Oriented Gradients HOG and the Haar Cascade Classifier. For VGA resolution, results reveal that the GPU implementation on this embedded system is 1.4x faster than the CPU for the HOG method and 2x for the Haar Cascade Classifier method.

关键词： Object detection Machine Learning Haar Cascade HOG Local feature descriptors GPU implementation OpenCV CUDA SoC Tegra X1 Jetson Nano

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Energy Consumption Optimization of Swin Transformer Based on Local Aggregation and Group-Wise Transformation 4

Energy Consumption Optimization of Swin Transformer Based on...

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4th international conference on computer Vision, image and Deep Learning, CVIDL 2023

作者： Liu, Yuhong Chen, Shengbo Lei, Zhou Wang, Peng School of Computer Engineering and Science Shanghai University Shanghai China

ISBN: (纸本)9798350326444

the Transformer is a natural language processing model that uses attention mechanisms, originally introduced by Google in 2017. Due to its excellent feature extraction capabilities, researchers in the industry have explored the application of Transformer in computer vision tasks. Following the success of the Vision Transformer in 2020, the Swin Transformer was introduced, which outperforms traditional convolutional neural networks on various benchmarks in the vision field. As a result, Swin Transformer has become a popular backbone for practical production applications. While Swin Transformer excels in accuracy, its large parameter size and high energy consumption pose challenges for deployment at the edge. Addressing this issue is crucial for the wide-scale adoption of Swin Transformer. Current research on energy consumption for Transformer-based models is still in its early stages. To reduce model size and energy consumption while preserving accuracy, this study focuses on model compression. Specifically, we propose a combination of group-wise transformation and local aggregation methods from traditional CNN models. By introducing local aggregation and group-wise transformation calculation methods while maintaining the original shifted window attention mechanism of Swin Transformer, the proposed approach effectively reduces the number of model parameters. Our experimental results show that the Swin-Transformer model trained with this method on an RTX-3090 graphics card can save up to 24% of energy, with an accuracy improvement of about 1%. © 2023 IEEE.

关键词： Energy utilization

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Dynamic YOLOv8n: A vehicle detection network model based on YOLOv8n 4

Dynamic YOLOv8n: A vehicle detection network model based on ...

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4th international conference on image processing and Intelligent Control, IPIC 2024

作者： Wei, Wei Liu, Yuxiu Yun, Jian Duan, Xiaodong School of Computer Science and Engineering Dalian Minzu University Dalian116650 China National Ethnic Affairs Commission of the People’s Republic of China Key Laboratory of Big Data Applied Technology Dalian Minzu University Dalian116650 China Dalian Key Laboratory of Digital Technology for National Culture Dalian Minzu University Dalian116650 China

ISBN: (纸本)9781510682313

For the vehicle edge computing platform, a huge model is difficult to achieve the requirements of real-time detection, which faces the challenges of high computational load and bad detection rate. In this paper, an improved YOLOv8n detection method is proposed, and a dynamic deformable convolution block (DDCNv2) is proposed in the YOLOv8n backbone network to improve the detection accuracy of the algorithm.A dynamic convolution module (KWConv) is introduced in the YOLOv8n. In addition, a multi-scale detector module is designed to reduce the number of parameters. We use the PASCAL VOC dataset and the MS COCO *** results show that compared with the existing YOLOv8n, the detection accuracy of the proposed model is improved by 5.1%, the FLOPs is reduced by 69.51%, and the model parameters is reduced by 8.64%, which proves the effectiveness and superiority of the proposed method. © 2024 SPIE.

关键词： Photons

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3D Printing Design Simulation of Ceramic Products Based on 3D image Reproduction Technology 4th

3D Printing Design Simulation of Ceramic Products Based on 3...

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4th international conference on Machine Learning, image processing, Network Security and Data Sciences (MIND)

作者： Yao, Lan Shanghai Art & Design Acad Shanghai Peoples R China

ISBN: (纸本)9783031243660;9783031243677

With the development of communication technology, people will be exposed to more and more graphics and images in the process of life andwork. Like using digital devices such as camera, scanner and camera to obtain images, but these instruments and equipment can only obtain two-dimensional image information of objects, which is completely insufficient. Inmany fields, three-dimensional information of objects is necessary. In this paper, the 3D printing design of ceramic products is simulated based on 3D image reproduction technology. the satisfaction of users with the ceramic visual effect and hand-held comfort produced by 3D image reproduction simulation technology is investigated by means of questionnaire, and the computer vision technology and stereo matching technology are compared. the results show that more than 85% of users are very satisfied with the ceramic visual effect and hand-held comfort of three-dimensional image reproduction simulation technology, and less than 5% of users are not satisfied;the satisfaction of ceramic visual effect produced by computer vision technology and stereo matching technology is less than 60%, and the hand-held comfort is less than 70%.

关键词： 3D image reproduction technology Ceramic products 3D printing design Simulation research

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Research on the Application of computer graphics and image Technology in Visual Communication 4

Research on the Application of Computer Graphics and Image T...

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4th international conference on computer Information Science and Artificial Intelligence, CISAI 2021

作者： Jiang, Songru Tianjin Academy of Fine Arts Tianjin300141 China

ISBN: (纸本)9781665406925

In recent years, the field of visual communication has developed rapidly, and computer graphics and image technology have been fully applied in it. Based on this, this article first expounds the relationship between computer graphics technology, visual communication, and clarifies the similarities and differences between computer graphics technology and visual communication. A simple analysis of computer graphics and image technology commonly used in the field of visual communication involves digital image enhancement technology and digital image restoration technology, and points out the application direction of computer image technology in visual communication. At the same time, in-depth discussion of the specific application steps of the technology is specifically related to image preprocessing, image beautification processing and other content, combined with simulation analysis can be determined. the computer graphics and image processing technology used in this article can get the highest peak signal-to-noise ratio in the shortest computing time. © 2021 IEEE.

关键词： Visual communication

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Research on digital Engraving Algorithms

Research on Digital Engraving Algorithms

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Electronic Information Engineering and computer Technology (EIECT), international conference on

作者： Siyu Song Peng Cao Faculty of Information Engineering Beijing Institute of Graphic Communication Beijing China

ISBN: (数字)9798331528850

ISBN: (纸本)9798331528867

the hand-carving plate-making technique is widely used in special printing, such as banknotes. However, its high technical requirements and time-consuming engraving process significantly limit the promotion and application of this technique, which possesses unique artistic expression effects. this study utilizes computer image processing algorithms to handle continuous tone images, simulating the effects of hand-carving to enhance plate-making speed and efficiency, thus providing significant research value. In this paper, we propose a digital carving algorithm based on the grayscale information of continuous tone images, combined with image segmentation algorithms and the modulation of carrier curve line widths, to construct an end-to-end digital carving image generation model. this model first employs a semantic segmentation algorithm to divide the image into segments, designing and generating carrier graphic grid lines based on the features of each segmented area. Subsequently, it modulates the feature parameters of the lines point by point according to the grayscale information of the original image, applying transformations such as rotation, distortion, and thickening. Finally, details such as cross-carving are added for enhanced rendering. the results indicate that the engraving effect of the output images achieved by this method closely resembles that of traditional digital carving, demonstrating its practical application value.

关键词： Hair Technical requirements Printing image color analysis Shape image synthesis Semantic segmentation Modulation Gray-scale Rendering (computer graphics)

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