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检索条件"任意字段=4th International Conference on Advanced Algorithms and Signal Image Processing, AASIP 2024"

共 127 条记录，以下是1-10 订阅

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Catch Fish Optimization Algorithm for Multi-threshold Segmentation in Esophageal Cancer CT image Analysis 24

Catch Fish Optimization Algorithm for Multi-Threshold Segmen...

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4th international conference on signal processing and Communication Technology, SPCT 2024

作者： Huang, Zongpeng Wei, Qinshao Qin, Peixiang Lu, Fanjing Huang, Changhui School of Medical Imaging Youjiang Medical University for Nationalities Guangxi Baise China School of Humanities and Management Youjiang Medical University for Nationalities Guangxi Baise China School of Languages and Cultures Youjiang Medical University for Nationalities Guangxi Baise China School of Medical Imaging Affiliated Hospital of Youjiang Medical University for Nationalities Guangxi Baise China

ISBN: (纸本)9798400710636

this paper proposes a multi-threshold image segmentation method based on the Catch Fish Optimization Algorithm (CFOA), specifically aimed at the analysis of esophageal cancer computerized tomography (CT) images. CFOA is a novel metaheuristic algorithm that simulates the fishing behavior of fishermen, possessing strong global search capabilities and flexible local search strategies, effectively balancing exploration and exploitation, and enhancing segmentation accuracy and efficiency. By combining with the Otsu method, CFOA demonstrates excellent performance in determining the optimal threshold, and is compared with advanced optimization algorithms such as MFO, NRBO, and RSA in experiments. the experimental results show that CFOA is competitive in key metric indicators such as Fitness, Peak signal-to-Noise Ratio (PSNR), and Structural Similarity Index (SSIM), especially showing superiority in handling the complexity of multimodal histograms. this study confirms the effectiveness and robustness of CFOA in the segmentation of esophageal cancer CT images, providing a new optimization tool for the field of image processing. © 2024 Copyright held by the owner/author(s).

关键词： Computerized tomography

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Deep insight of medical images segmentation and classification by deep learning 4th

Deep insight of medical images segmentation and classificati...

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4th international conference on Computational Methods in Science and Technology, ICCMST 2024

作者： Arora, Amit Kumar Kaur, Amanpreet CSE IKGPTU Punjab India Mohali India

ISBN: (纸本)9781032911571

image segmentation is a crucial process in picture analysis and processing, affecting object presentation, description, and classification. It is essential for identifying, characterizing, and visualizing regions of interest in medical images. Manual segmentation by radiologists is arduous and time-consuming, and its accuracy is often compromised due to the growing number of medical imaging modalities and the volume of images. therefore, it is crucial to evaluate existing picture segmentation approaches using automated algorithms that offer high accuracy and minimize user intervention, especially in medical photographs. Accurately demarcate and extract the anatomical framework or ROI for independent visualization. this paper will embark on the importance of image segmentation in decision-making information extraction, especially in this technological era. Some of the main and advanced application areas with recent research breakthroughs that have proved very significant in the field of medical imaging will be discussed. © 2025 the Author(s).

关键词： image segmentation

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Computer graphics and image processing techniques based on visual communication design 4

Computer graphics and image processing techniques based on v...

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4th international conference on Computer Vision, Application, and Algorithm, CVAA 2024

作者： Chen, Zhaoguo College of Arts Shandong Agricultural Engineering University Shandong Province Jinan250103 China

ISBN: (数字)9781510687622

ISBN: (纸本)9781510687615

To fully harness the capabilities of computer graphics and image processing technologies and elevate the quality of visual communication design, this paper presents a comprehensive suite of innovative methodologies. Firstly, the fundamental principles of primary colors are utilized to formulate a series of vector functions, facilitating the precise calculation of error distances and the establishment of an intricate visual communication zoning model. Subsequently, through the exhaustive extraction of pertinent feature information from graphics and images, we achieve the scientific encoding of coefficient-constrained features and determine the corresponding hyperplanes to acquire the relevant parameters for visual communication. Eventually, the implementation of advanced design image expression algorithms markedly enhances the effectiveness of visual communication image representation. the empirical findings reveal that these visual communication design methods exhibit remarkable reliability and feasibility, effectively boosting image recognition accuracy across four distinct image categories with varying levels of complexity, thereby yielding exceptional visual communication outcomes. © 2025 SPIE.

关键词： Design Visual communications Visualization Computer graphics image processing image storage Color image segmentation image enhancement

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Research on high accuracy classification of temperature signals based on OFDR technology and EfficientNet 4

Research on high accuracy classification of temperature sign...

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4th international conference on advanced Manufacturing Technology and Electronic Information, AMTEI 2024

作者： Shang, Chuanyin Li, Peng Tong, Zhengrong Wang, Hao Li, Sibo Tianjin Key Laboratory of Thin Film Electronics and Communication Devices Engineering Research Center for Optoelectronic Devices and Communication Technology the Ministry of Education School of Integrated Circuit Science and Engineering Tianjin University of Technology Tianjin300384 China

ISBN: (数字)9781510688247

ISBN: (纸本)9781510688230

the development of machine learning is driving revolutionary changes and unprecedented opportunities across various industries. this paper introduces a new temperature monitoring method that combines the efficient deep learning model EfficientNet with Optical Frequency Domain Reflectometry (OFDR). We utilize distributed fiber-optic sensing technology based on OFDR to collect one-dimensional temperature signals under different temperature conditions, which we then transform into a two-dimensional image format suitable for machine learning processing. the dataset is subsequently trained using the EfficientNet deep learning model. the results show that the trained model achieves a high accuracy rate of 97.5% on the test dataset. this research not only demonstrates the feasibility of efficiently and accurately monitoring temperature changes but also provides new solutions and technological pathways for areas such as environmental monitoring, industrial automation, and safety systems. © 2025 SPIE.

关键词： Education and training Data modeling Performance modeling Fiber optics sensors Machine learning Matrices Fiber optics image processing Reliability signal processing

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Research on optical image quality assessment under strong light interference 4

Research on optical image quality assessment under strong li...

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4th international Computational Imaging conference, CITA 2024

作者： Wang, Si-Yu Feng, Yun-Song Jin, Wei Zhou, Chang-Qi Liu, Li-Ping Chen, You-Cai Key Laboratory of Infrared Low Temperature Plasma of Anhui Province National University of Defense Technology Hefei230037 China Advanced Laser Technology Laboratory of Anhui Province National University of Defense Technology Hefei230037 China State Key Laboratory of Pulsed Power Laser Technology National University of Defense Technology Hefei230037 China

ISBN: (纸本)9781510688834

In the face of technological advancements, the military domain has witnessed the emergence of diverse innovative weaponry, with optical applications in weaponry playing a pivotal role. To counteract the threat of enemy optical-guided weapons on the battlefield, it is imperative to implement countermeasures. Strong light interference stands out as a prevalent optical countermeasure technique. To achieve better strong light interference effects, we need to conduct a quantitative analysis of the strong light interference effectiveness, which is the evaluation of image quality after interference. image quality assessment is a critical process that involves comparing images using specialized methods, which can be categorized into subjective and objective evaluations. Subjective evaluation, which relies on human analysis and judgment of image similarity, is labor-intensive and requires a significant number of experts, limiting its practical application. In contrast, objective evaluation leverages computational power to execute algorithms that provide a quantitative analysis of images. this approach transforms images from an intractable entity into a form that can be systematically analyzed and quantified. this study employs MATLAB software to harness the power of five distinct algorithms: Mean Hash Algorithm, Difference Hash Algorithm, Perceptual Hash Algorithm, Histogram Cosine Similarity Algorithm, and Histogram Bias Coefficient Algorithm. these algorithms are adept at processing images and converting them into numerical representations of similarity. By employing the respective program translations of these algorithms, we can quantify the degree of image similarity, thereby facilitating a comprehensive assessment of image quality. this quantitative approach not only streamlines the evaluation process but also enhances the accuracy and reliability of the results. © 2025 SPIE.

关键词： MATLAB

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advanced Model for Oracle Bone image Denoising and Feature Extraction Based on Multi-Algorithm Integration and Wavelet Transform 24

Advanced Model for Oracle Bone Image Denoising and Feature E...

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Proceedings of the 2024 4th international conference on Computational Modeling, Simulation and Data Analysis

作者： Yufen Zhang Zile Xu Mengguo Zhang Lin Yang Xudong Wang College of Science University of Shanghai for Science and Technology Shanghai China Department of Water Conservancy Engineering Henan Vocational College of Water Conservancy and Environment Zhengzhou Henan China School of Health Science and Engineering University of Shanghai for Science and Technology Shanghai China

ISBN: (纸本)9798400711831

As an important part of ancient Chinese cultural heritage, oracle bone image has important historical and cultural value. However, due to the unique image features and noise interference, effective image processing and analysis are still facing great challenges. In this paper, we propose an advanced model for oracle bone image denoising and feature extraction based on multi-algorithm ensemble and wavelet transform. Firstly, wavelet transform is used for image denoising to effectively remove noise and retain key image features. then, the image contrast is enhanced by gray inversion and binarization, and the image structure is simplified by skeletonization, which lays the foundation for subsequent feature extraction. In the frequency domain analysis, Fourier transform is applied to reveal the spectral characteristics of the image, so as to understand and analyze the image data more deeply. In order to accurately determine the edges and corners of oracle images, this study compared several edge detection algorithms (such as Canny, Sobel, and Prewitt) and corner detection algorithms (such as Harris, SURF, and ORB). the results show that Canny performs well in edge detection and noise suppression, while SURF and ORB are more suitable for real-time processing and resource constrained environments. this model provides a new method for the digital preservation and dissemination of oracle bone images, and establishes a benchmark for the optimization design of algorithms in the field of image analysis.

关键词： Binarization 3

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Color polarization image fusion algorithm based on wavelet transform 4

Color polarization image fusion algorithm based on wavelet t...

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4th international conference on advanced algorithms and signal image processing, aasip 2024

作者： Pan, Yuhang Zhao, Haili School of Electronic Information Engineering Changchun University of Science and Technology Changchun China

ISBN: (数字)9781510682818

ISBN: (纸本)9781510682801

To enhance the quality and contrast of color polarization images, this paper proposes a novel color polarization image fusion algorithm based on wavelet transform (WTCPI). the method begins by preprocessing four images captured at different polarization angles to generate a polarization intensity (I) image and a degree of linear polarization (DoLP) image using the Stokes vector method. Wavelet decomposition is then applied to these images to obtain their high-frequency and low-frequency components. the low-frequency components are fused using a weighted average method, while the high-frequency components are fused by taking the maximum of their absolute values. Finally, the fused images are reconstructed. Experimental results demonstrate that the proposed algorithm significantly improves subjective visual comfort and outperforms existing methods across all objective evaluation metrics. © 2024 SPIE.

关键词： image fusion

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Review of image calibration and distortion correction based on internal threads 4

Review of image calibration and distortion correction based ...

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4th international conference on advanced algorithms and signal image processing, aasip 2024

作者： Yuan, Haotian Dou, Xiaohan Xue, Chengqi Zhao, Xuanyi Luo, Chengjie Xu, Zihan Jiang, Zhihao Yangtze University No.1 Nanhuan Road Hubei Province Jingzhou City China

ISBN: (数字)9781510682818

ISBN: (纸本)9781510682801

this paper presents a comprehensive review of image calibration and distortion correction techniques based on internal threads, focusing on their principles, methods, applications, and challenges. Internal threads serve as unique calibration markers due to their invariability and high detectability, providing essential parameters for image distortion correction. the review highlights the effectiveness of these techniques in enhancing accuracy and reliability in various high-precision applications, such as industrial inspection and medical imaging. It also addresses the computational complexity, sensitivity to initial parameters, and the need for high-quality images. the paper aims to offer valuable insights and references for future research and development in image processing technologies, promoting their broader application and advancement. © 2024 SPIE.

关键词： image enhancement

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Space observation dim target detection of star image background 4

Space observation dim target detection of star image backgro...

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4th international conference on advanced algorithms and signal image processing, aasip 2024

作者： Yin, Hang Zhang, Jiaqi Rong, Youhui Liu, Mengya Space Engineering University Beijing101407 China

ISBN: (数字)9781510682818

ISBN: (纸本)9781510682801

Detection of dim target in star image background poses significant challenges due to the presence of noise and variations in object intensities. this paper presents an improvement to conventional pipeline filtering algorithms through the implementation of energy accumulation technique. By accumulating energy from multiple sources, the improved precision achieved in identifying dim targets within intricate celestial environments. the improvement also integrates background suppression and wavelet transform denoising methods to enhance detection efficacy. through a combination of comprehensive simulations and empirical validation, the enhanced algorithm demonstrates higher success rates and greater robustness in dim target detection compared to conventional methods. the results indicate that the improved algorithm offers enhanced precision in identifying dim target in star image background, thereby advancing capabilities for astronomical research and space exploration endeavors. © 2024 SPIE.

关键词： Space research

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An optimized YOLOv8-based algorithm for remote sensing image detection 4

An optimized YOLOv8-based algorithm for remote sensing image...

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4th international conference on advanced algorithms and signal image processing, aasip 2024

作者： Xie, Pengdong Situ, Guoqiang School of Electronic and Information Engineering Lanzhou Jiaotong University Lanzhou730073 China

ISBN: (数字)9781510682818

ISBN: (纸本)9781510682801

Target detection technology in remote sensing images holds significant importance in fields such as signal processing and radar imaging. However, due to the substantial influence of electromagnetic wave scattering characteristics on remote sensing image, the size of objects to be detected undergoes considerable changes, increasing the difficulty of detection. At the same time, the extensive background information contains confusing geographical elements, severely affecting the detection performance. We use YOLOv8 as the baseline model and employ Swin Transformer as the backbone structure to enhance the model's ability to connect context. Additionally, Coordinate Attention is added at the end of the backbone to deal with complex backgrounds, concentrating more weight on our points of interest. Finally, to detect smaller targets, we incorporate a smaller scale detection head to capture more subtle points of interest. through experiments, our model's mAP@0.5, Recall, and Precision reached 0.628, 0.583, and 0.691, respectively, far surpassing several existing advanced models. © 2024 SPIE.

关键词： Radar imaging

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