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检索条件"任意字段=2023 IEEE International Conference on Image Processing and Computer Applications, ICIPCA 2023"

共 4812 条记录，以下是331-340 订阅

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Blind image Separation Using Composite Criteria based on Statistical Information and Sparse Representation 12

Blind Image Separation Using Composite Criteria based on Sta...

引用

12th international conference on image processing Theory, Tools and applications, IPTA 2023

作者： Boudjenouia, Fouad Abed-Meraim, Karim Chetouani, Aladine Jennane, Rachid Polytechnic Military School Algiers Algeria University of Orléans Prisme Laboratory Orléans France University of Orléans Idp Institute UMR-CNRS 7013 Orléans France

ISBN: (纸本)9798350325416

This paper deals with blind image separation by exploiting the statistical characteristics of the mixtures (information related to the sources independence) with the sparsity of the signals. More precisely, we investigate and compare the gain that can be reached by considering two different signal properties, namely the statistical independence and the sparse representation. These properties are considered in a 'dual' as well as in a 'hybrid' mode. Both approaches are compared, simulation and experimental results demonstrate the efficiency of the proposed methods. © 2023 ieee.

关键词： Blind source separation

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Cloud-Mobile Video Super-Resolution Method Based on Deep Learning

Cloud-Mobile Video Super-Resolution Method Based on Deep Lea...

引用

2023 ieee international conference on Electrical, Automation and computer Engineering, ICEACE 2023

作者： Zhou, Jing Zheng, Yang Yu, Songbin Yan, Zhijun Yuan, Huishen Business Department Beijing China

ISBN: (纸本)9798350309614

With the rapid popularity of short video applications and the rise of streaming media platforms, video images have become an important medium for people's daily communication, and users' requirements for image quality are getting higher and higher. In order to improve the image quality of mobile devices or web applications, the image Super-Resolution (SR) algorithm is often used to help improve the user experience. In order to effectively solve the problems of image deterioration caused by limited cloud-mobile transmission bandwidth, difficult model deployment, high energy consumption, and slow inference speed, this paper proposes a lightweight image super-resolution model based on attention mechanism and multi-scale residual network. First of all, the multi-scale characterization ability of the algorithm model is enhanced by combining dense connection and channel attention mechanism to improve the performance of image super-score reconstruction. Secondly, the loss function of mean variance and total variation is used in the training process to eliminate the impact of noise in the reconstruction process. Finally, through experimental analysis and comparison of results, it is concluded that the proposed cloud-mobile video super-resolution method has better image reconstruction performance and faster processing speed. © 2023 ieee.

关键词： Deep learning image reconstruction super-resolution

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Dual Illumination image Enhancement Using Automated MSRCR and Illumination Estimation 5

Dual Illumination Image Enhancement Using Automated MSRCR an...

引用

5th ieee international conference on Artificial Intelligence in Engineering and Technology, IICAIET 2023

作者： Brillantes, Allysa Kate Sybingco, Edwin Bandala, Argel Billones, Robert Kerwin Fillone, Alexis Dadios, Elmer Department of Electronics and Computer Engineering 2401 Taft Avenue Malate Manila Philippines Department of Manufacturing Engineering and Management 2401 Taft Avenue Malate Manila Philippines Department of Civil Engineering 2401 Taft Avenue Malate Manila Philippines Tntelligent Systems Laboratory 2401 Taft Avenue Malate Manila Philippines

ISBN: (纸本)9798350304152

images taken in low-light environments like nighttime or cloudy weather are not conducive to monitoring and fail to fulfill the requirements of applications such as image processing and computer vision. This paper focuses on improving a dual illumination image enhancement algorithm to achieve better image quality and reduce the processing time of producing an enhanced image. The underexposed correction image was produced using Automated Multiscale Retinex Color Restoration while the overexposed correction image was produced using illumination estimation, the corrected images were combined to generate a better-quality image. The system was assessed using the metrics: BRISQUE, NIQE, MDM, and CEIQ, and achieved a BRISQUE value of 18.628, NIQE value of 1.744, MDM value of 0.968, and CEIQ value of 3.615. © 2023 ieee.

关键词： image enhancement

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Prototype of a System to Assist the Urologist in the Recognition of Urinary Bladder Tumors in MRI images 10

Prototype of a System to Assist the Urologist in the Recogni...

引用

10th international conference on Soft Computing and Machine Intelligence (ISCMI)

作者： Martinez, Ares Ulises Juarez Lomas, Jaime Hugo Puebla Talamantes, Jose Felix Serrano ESCOM IPN Dept Syst Engn Computat Mexico City DF Mexico CIDETEC IPN Virtual Real Lab Mexico City DF Mexico

ISBN: (纸本)9798350359374

The proposal aims to develop a prototype system to detect possible bladder tumors. The system Will use image processing techniques, computer vision, segmentation, pattern recognition and machine learning. The prototype Will load images of the urinary bladder (hollow, distensible muscular organ) and obtain a classification of possible bladder tumors.

关键词： urinary bladder image processing artificial intelligence segmentation and machine learning

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A Novel Approach for image Background Elimination

A Novel Approach for Image Background Elimination

引用

2023 ieee international conference on Research Methodologies in Knowledge Management, Artificial Intelligence and Telecommunication Engineering, RMKMATE 2023

作者： SenthilPandi, S. Naresh Kumar, A. Nitheesh Kumar, B. Paulraj, D. Department of Computer Science and Engineering Rajalakshmi Engineering College Chennai India Department of Computer Science and Engineering R.M.K. Engineering College Chennai India

ISBN: (纸本)9798350305708

A convenient and effective mobile tool for enabling the painless removal of background from photographs is the image Background Remover Android Application. The essential job of background removal in image analysis and computer vision has applications in computer graphics, object detection, and image editing. This study compares and contrasts cutting-edge background removal algorithms and approaches in order to assess their benefits, drawbacks, and suitability for various uses. The application enables users to get precise and eye-catching results by utilizing cutting-edge algorithms for image processing and interactive features. Users using the app can upload pictures from the device's storage or take brand-new ones with the camera. Then, a variety of background removal techniques are used. Then, to precisely distinguish between foreground and background regions, a variety of background removal techniques are used, such as color-based thresholding, Grab-cut and semantic segmentation based on deep learning. Using interactive editing tools, users have the freedom to manually improve the segmentation. The program additionally supports real-time processing, enabling users to see a live preview of background removal. Users may easily generate captivating photographs with smooth backgrounds removed thanks to the results being displayed through an easy and responsive user interface. The application shows its effectiveness, adaptability, and promise in practical uses in processing images and artistic production of content through careful analysis and user input. © 2023 ieee.

关键词： Background Removal algorithms Semantic Segmentation Thresholding

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Design and Realization of Intelligent image Recognition System Based on computer 1

Design and Realization of Intelligent Image Recognition Syst...

引用

1st international conference on computer Graphics and image processing, CGIP 2023

作者： Pan, Jiheng Liaoning Urban Construction Technical College Liaoning Shenyang China

ISBN: (纸本)9798350333183

The update of modern intelligent technology has driven the progress of computer related technology. The tide of technological revolution is impacting the economic system all over the world. The emergence of information technology has helped the intelligent information industry break through the bottleneck period of traditional development. computer image intelligent recognition technology is gradually mature. This form puts forward higher requirements for China's economic construction. On this basis, the design of image recognition system has gradually become the main research object of experts. This paper explains the relevant theories of image recognition technology. Finally, the design and implementation of image recognition system are proposed. © 2023 ieee.

关键词： image recognition

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New Type-2 Fuzzy Logic Algorithm Based image Segmentation for Medical Imaging applications 9

New Type-2 Fuzzy Logic Algorithm Based Image Segmentation fo...

引用

9th ieee international conference on Smart Structures and Systems, ICSSS 2023

作者： Sangeetha, S. Latha, B. Anna University Veltech Multitech Dr. Rangarajan Dr. Sakunthala Engineering College Department of Information Technology Chennai India Sri Sairam Engineering College Department of Computer Science and Engineering Chennai India

ISBN: (纸本)9798350384208

Medical image segmentation is a plan that has a lot of potential. The achievement of automated picture segmentation makes it simple to gather biomedical and anatomical information. In terms of the subject, more study and work have increased efficacy. In the field of image processing, this work provides a type-2 fuzzy system-based image application. computer aided diagnosis and medical image analysis both heavily rely on segmentation. This study presents a fuzzy type 2 algorithm based automated threshold selection method for the division of therapeutic pictures. It has been established that fuzzy set theory may be an effective tool for recitation surroundings when the facts are unclear or inaccurate. The algorithms have been put into practice and evaluated using brain MRI (magnetic resonance imaging) images. The outcomes have been evaluated and documented. The comparison of the controller's efficiency of CNN has 92%. © 2023 ieee.

关键词： image segmentation

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Inverse Quantum Fourier Transform Inspired Algorithm for Unsupervised image Segmentation

Inverse Quantum Fourier Transform Inspired Algorithm for Uns...

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37th ieee international Parallel and Distributed processing Symposium (IPDPS)

作者： Akinola, Taoreed Li, Xiangfang Wilkins, Richard Obiomon, Pamela Qian, Lijun Prairie View A&M Univ Dept Elect & Comp Engn Prairie View TX 77446 USA

ISBN: (纸本)9798350311990

image segmentation is a very popular and important task in computer vision. In this paper, inverse quantum Fourier transform (IQFT) for image segmentation has been explored and a novel IQFT-inspired algorithm is proposed and implemented by leveraging the underlying mathematical structure of the IQFT. Specifically, the proposed method takes advantage of the phase information of the pixels in the image by encoding the pixels' intensity into qubit relative phases and applying IQFT to classify the pixels into different segments automatically and efficiently. To the best of our knowledge, this is the first attempt of using IQFT for unsupervised image segmentation. The proposed method has low computational cost comparing to the deep learning based methods and more importantly it does not require training, thus make it suitable for real-time applications. The performance of the proposed method is compared with K-means and Otsuthresholding. The proposed method outperforms both of them on the PASCAL VOC 2012 segmentation benchmark and the xVIEW2 challenge dataset by as much as 50% in terms of mean Intersection-Over-Union (mIOU).

关键词： Inverse Quantum Fourier Transform computer Vision image Segmentation

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Efficient Approximate 8-Bit Binary Parallel Subtractor Circuit: Design, Analysis, and Application in Negative image Generation 9

Efficient Approximate 8-Bit Binary Parallel Subtractor Circu...

引用

9th international conference on Signal processing and Communication, ICSC 2023

作者： Gupta, Sanjiv Kumar Tiwari, Manish Dhawan, Amit Jha, Sumit Kumar Department of Electronics and Communication Engineering Motilal Nehru National Institute of Technology Allahabad Uttar Pradesh Prayagraj211004 India

ISBN: (纸本)9798350383201

In the field of image processing and computer vision, negative imaging is vital for applications like medical imaging, art, and data enhancement. This paper introduces an efficient approach for negative image creation using an approximate 8-bit binary parallel subtractor (ABPS) circuit. The ABPS circuit reduces area usage by 33% and significantly cuts delay by 68.4% compared to conventional subtractor. The ABPS circuit balances precision and speed, making it ideal for tasks where small errors are acceptable. The efficacy of ABPS is demonstrated through its successful application in generating negative images, underscoring its performance. © 2023 ieee.

关键词： Computational efficiency

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Generation of Digital Reconstruction Radiation image and Display System Design

Generation of Digital Reconstruction Radiation Image and Dis...

引用

image processing and computer applications (icipca), ieee international conference on

作者： Jiaying Zhang Huifeng Kong Lili Cai Su Zhou School of Biomedical Engineering Guangzhou Xinhua University Guangzhou China

Digitally reconstructed radiography (DRR) plays an important role in the treatment planning system (TPS) and many medical imaging applications such as 2D / 3D image registration. DRR generation technology is one of the core technologies of TPS. In this paper, the DRR image is generated by ray projection method based on volume rendering, and the display interface is designed to visualize the results. The medical image data set is resampled by reading the file header information of the medical image data set and the simulated light source projection distance, data set image spacing and pixel size are calculated by establishing the relevant coordinate transformation function and interpolation function. Finally, the DRR image results are displayed on the interface designed by the QT framework. The similarity is measured between the DRR image generated by ray casting method and the DRR image obtained by clinical TPS. The average of root mean square error(RMSE) is 0.25,and the peak signal-to-noise ratio(PSNR) is greater than 30 decibels and the structural similarity image measurement(SSIM) is positive. The results can provide the core technology for the subsequent DRR image display system and 2D / 3D registration. As well, the display interface can normally display the three orthographic views and DRR results of CT sequence images. It can be seen that the DRR image generated by the algorithm used in this paper has the same quality as the DRR image in clinical application, which proves the effectiveness of the algorithm and the good imaging effect.

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