2023 International Conference on Computer Graphics and Image Processing (CGIP)最新文献_第2页

Research on Automatic Text Summarization Based on Extractive Method 基于抽取方法的自动文本摘要研究

2023 International Conference on Computer Graphics and Image Processing (CGIP) Pub Date : 2023-01-01 DOI: 10.1109/CGIP58526.2023.00022

Rong Jing, F. Wan

引用次数: 0

Determining region color by using maximum colorfulness 使用最大色彩度确定区域颜色

2023 International Conference on Computer Graphics and Image Processing (CGIP) Pub Date : 2023-01-01 DOI: 10.1109/CGIP58526.2023.00010

Youngha Chang, S. Saito

引用次数: 1

Arm Injury Classification on a Small Custom Dataset Using CNNs and Augmentation 基于cnn和增强的小型自定义数据集手臂损伤分类

2023 International Conference on Computer Graphics and Image Processing (CGIP) Pub Date : 2023-01-01 DOI: 10.1109/CGIP58526.2023.00014

Ahmad Faiz Bin Nor’azam, Y. Mitani

引用次数: 0

Copyright Page 版权页

2023 International Conference on Computer Graphics and Image Processing (CGIP) Pub Date : 2023-01-01 DOI: 10.1109/cgip58526.2023.00003

引用次数: 0

Optimal Design of Color Laparoscopic Super-Resolution Image Quality Based on Generative Adversarial Networks 基于生成对抗网络的彩色腹腔镜超分辨率图像质量优化设计

2023 International Conference on Computer Graphics and Image Processing (CGIP) Pub Date : 2023-01-01 DOI: 10.1109/CGIP58526.2023.00009

Norifumi Kawabata, Toshiya Nakaguchi

{"title":"Optimal Design of Color Laparoscopic Super-Resolution Image Quality Based on Generative Adversarial Networks","authors":"Norifumi Kawabata, Toshiya Nakaguchi","doi":"10.1109/CGIP58526.2023.00009","DOIUrl":"https://doi.org/10.1109/CGIP58526.2023.00009","url":null,"abstract":"The Generative Adversarial Networks (GAN) is unsupervised learning enabled to transform according to data characteristics, though this generate unreal data by learning characteristics from data. As past our study, we discussed from the viewpoint of image quality for super-resolution of color laparoscopic image including SRCNN (Super-Resolution Convolutional Neural Network). However, it was not enough to compare to other neural network methods in our discussion. We consider that it is possible to support the medical image diagnosis by measuring whether the difference of both neural network method and image contents is affected or not for image quality. In this paper, first we carried out the objective image quality assessment by designing optimally of color laparoscopic super-resolution image using Generative Adversarial Networks (GAN). And then, we discussed for performance between methods comparing to result of SRCNN. On the other hand, from a view of information science, we consider that we need to verify experimentally for affect between network learning effect and generated image, and then to improve method. Therefore, we also discussed relationship between image quality and learning effect in color laparoscopic image generation using SRGAN.","PeriodicalId":286064,"journal":{"name":"2023 International Conference on Computer Graphics and Image Processing (CGIP)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125020649","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Design and Realization of Intelligent Image Recognition System Based on Computer 基于计算机的智能图像识别系统设计与实现

2023 International Conference on Computer Graphics and Image Processing (CGIP) Pub Date : 2023-01-01 DOI: 10.1109/CGIP58526.2023.00016

Jiheng Pan

引用次数: 0

Development of Computerized 3D Image Parametric Analysis System Based on BIM 基于BIM的计算机三维图像参数化分析系统的开发

2023 International Conference on Computer Graphics and Image Processing (CGIP) Pub Date : 2023-01-01 DOI: 10.1109/CGIP58526.2023.00020

Ai-hua Zhang, Haiyan Xu

{"title":"Development of Computerized 3D Image Parametric Analysis System Based on BIM","authors":"Ai-hua Zhang, Haiyan Xu","doi":"10.1109/CGIP58526.2023.00020","DOIUrl":"https://doi.org/10.1109/CGIP58526.2023.00020","url":null,"abstract":"Traditional computer 3D modelling techniques require a lot of manpower, material and time, and do not provide multiple information at the same time. BIM technology is a kind of software based on model development, and the 3D image parametric analysis system designed based on this technology can visualise design, reduce the miscommunication of information between designers and viewers, convert the data processing required in complex structured design into various kinds of graphical images that can be presented visually; check the spatial conflicts of components; simulate the construction progress, collaborate with multi-professionals; informatise project management, make it efficient, and obtain visual results quickly. It can check the spatial conflicts of components, simulate construction progress and collaborate with multi-disciplinary cooperation, inform the project management and make it efficient, and obtain visual results quickly to meet the needs of users. It also enables three-dimensional modelling functions, giving it certain rules and specifications, among other features. In addition the system uses a variety of information, which is of great value in engineering applications.","PeriodicalId":286064,"journal":{"name":"2023 International Conference on Computer Graphics and Image Processing (CGIP)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115866537","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Image Watermarking Algorithm Based on q-logarithm Component 基于q-对数分量的图像水印算法

2023 International Conference on Computer Graphics and Image Processing (CGIP) Pub Date : 2023-01-01 DOI: 10.1109/CGIP58526.2023.00021

Piyanart Chotikawanid, T. Amornraksa

{"title":"Image Watermarking Algorithm Based on q-logarithm Component","authors":"Piyanart Chotikawanid, T. Amornraksa","doi":"10.1109/CGIP58526.2023.00021","DOIUrl":"https://doi.org/10.1109/CGIP58526.2023.00021","url":null,"abstract":"A new embedding component for image watermarking in the spatial domain is presented in this paper as a solution to copyright protection and to verify the real owner of digital image. The embedding component called q-logarithm is extracted from a host color image, and is used directly to embed watermark information. In the extraction process of the embedded watermark, the original version of non-watermarked component is first estimated from the average value of watermarked components in a small image area, so that the blind watermark extraction can be achieved. The watermarked image’s quality is assessed by weight Peak Signal to Noise Ratio (wPSNR), and the extracted watermark’s accuracy is assessed by Bit Correction Error (BCR). Investigations for optimal parameters are carried out to obtain q value that gives the most accurate extracted watermark. In the experiments, the performance of the proposed method is compared to the relevant three previous methods. A well-known benchmark called Stirmark is also used to assess the robustness of the embedded watermark. It is shown accordingly that the proposed method can achieve better performance in terms of accuracy and robustness even under attacks.","PeriodicalId":286064,"journal":{"name":"2023 International Conference on Computer Graphics and Image Processing (CGIP)","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122071928","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0