Journal of Imaging Science and Technology最新文献_第5页

Comparison of Pigment Classification Algorithms on Non-Flat Surfaces using Hyperspectral Imaging 基于高光谱成像的非平坦表面色素分类算法比较

4区计算机科学

Journal of Imaging Science and Technology Pub Date : 2023-09-01 DOI: 10.2352/j.imagingsci.technol.2023.67.5.050405

Dipendra J. Mandal, Marius Pedersen, Sony George, Clotilde Boust

{"title":"Comparison of Pigment Classification Algorithms on Non-Flat Surfaces using Hyperspectral Imaging","authors":"Dipendra J. Mandal, Marius Pedersen, Sony George, Clotilde Boust","doi":"10.2352/j.imagingsci.technol.2023.67.5.050405","DOIUrl":"https://doi.org/10.2352/j.imagingsci.technol.2023.67.5.050405","url":null,"abstract":"Cultural heritage objects, such as paintings, provide valuable insights into the history and culture of human societies. Preserving these objects is of utmost importance, and developing new technologies for their analysis and conservation is crucial. Hyperspectral imaging is a technology with a wide range of applications in cultural heritage, including documentation, material identification, visualization and pigment classification. Pigment classification is crucial for conservators and curators in preserving works of art and acquiring valuable insights into the historical and cultural contexts associated with their origin. Various supervised algorithms, including machine learning, are used to classify pigments based on their spectral signatures. Since many artists employ impasto techniques in their artworks that produce a relief on the surface, i.e., transforming it from a flat object to a 2.5D or 3D, this further makes the classification task difficult. To our knowledge, no previous research has been conducted on pigment classification using hyperspectral imaging concerning an elevated surface. Therefore, this study compares different spectral classification techniques that employ deterministic and stochastic methods, their hybrid combinations, and machine learning models for an elevated mockup to determine whether such topographical variation affects classification accuracy. In cultural heritage, the lack of adequate data is also a significant challenge for using machine learning, particularly in domains where data collection is expensive, time-consuming, or impractical. Data augmentation can help mitigate this challenge by generating new samples similar to the original. We also analyzed the impact of data augmentation techniques on the effectiveness of machine learning models for cultural heritage applications.","PeriodicalId":15924,"journal":{"name":"Journal of Imaging Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134995368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Color Performance Review (CPR): A Color Performance Analyzer for Endoscopy Devices 彩色性能评价（CPR）：用于内窥镜设备的彩色性能分析仪

IF 1 4区计算机科学

Journal of Imaging Science and Technology Pub Date : 2023-09-01 DOI: 10.2352/j.imagingsci.technol.2023.67.5.050406

Wei-Chung Cheng

引用次数: 0

An Appearance Reproduction Framework for Printed 3D Surfaces 打印3D表面的外观再现框架

4区计算机科学

Journal of Imaging Science and Technology Pub Date : 2023-09-01 DOI: 10.2352/j.imagingsci.technol.2023.67.5.050413

Tanzima Habib, Phil Green, Peter Nussbaum

引用次数: 0

Grey Balance in Cross Media Reproductions 跨媒体复制中的灰平衡

4区计算机科学

Journal of Imaging Science and Technology Pub Date : 2023-09-01 DOI: 10.2352/j.imagingsci.technol.2023.67.5.050411

Gregory High, Peter Nussbaum, Phil Green

{"title":"Grey Balance in Cross Media Reproductions","authors":"Gregory High, Peter Nussbaum, Phil Green","doi":"10.2352/j.imagingsci.technol.2023.67.5.050411","DOIUrl":"https://doi.org/10.2352/j.imagingsci.technol.2023.67.5.050411","url":null,"abstract":"Grey balance plays an important role in determining the device values needed to reproduce colours which appear achromatic throughout the tonal range. However, complete observer adaptation to the media white rarely occurs, and these designated device values can still appear non-neutral. This poses a problem for cross-media reproductions, where a mismatch in neutral colours is often the most noticeable difference between them. This paper presents two related experiments which investigate a means of gaining better visual agreement between reproductions which have different background colours or media whites. The first quantifies the degree of adjustment (the degree of media relative transform) needed to make an appearance match between grey patches on a white background and on background colours of various hues and colourfulness. It was found that the degree of adjustment was near-linearly related to the luminance of the patch itself, with lighter patches requiring greater adjustment towards the background colour. Neither the hue nor the chroma of the patch’s background had any significant effect on the underlying function. In the second experiment, this concept is applied to pictorial images on paper-coloured backgrounds. Three pixelwise rendering strategies were compared. In side-by-side viewing, the adaptive control of neutrals outperformed the media relative transform in all cases. Even for modest differences in paper colour (ΔEab of 3), images with significant neutral content benefited from the adaptive approach.","PeriodicalId":15924,"journal":{"name":"Journal of Imaging Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135588789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Matrix R-based Visual Response to Optimal Colors and Application to Image Color Gamut Expansion 基于矩阵r的最优颜色视觉响应及其在图像色域扩展中的应用

4区计算机科学

Journal of Imaging Science and Technology Pub Date : 2023-09-01 DOI: 10.2352/j.imagingsci.technol.2023.67.5.050414

Hiroaki Kotera

{"title":"Matrix R-based Visual Response to Optimal Colors and Application to Image Color Gamut Expansion","authors":"Hiroaki Kotera","doi":"10.2352/j.imagingsci.technol.2023.67.5.050414","DOIUrl":"https://doi.org/10.2352/j.imagingsci.technol.2023.67.5.050414","url":null,"abstract":"The optimal colors with maximum chroma at constant lightness present an ideal target for the colorants pursuing the ultimate wide color gamut. MacAdam proved that optimal colors are composed of square pulse-shaped spectra with at least two tansition wavelengths λ1 and λ2 whose reflectances change from 0 to 1 or 1 to 0. The optimal color gamut is created from two-types, a convex-type with reflectance 1.0 in w = λ1 ∼ λ2 and 0.0 otherwise, or a concave-type with reflectance 0.0 in w = λ1 ∼ λ2 and 1.0 otherwise. It takes a high computation cost to search the optimal color candidates in high precision and to create the 3D color gamut. In addition, the human visual spectral responses to the optimal color spectra remain unknown. This paper (1) proposes an alternative simple method for creating the optimal color gamut with GBD (Gamujt Boundary Descriptor) technique, and (2) clarifies how human vision spectrally respond to the optimal colors based on Matrix-R theory, for the first time which was unknown until now, and (3) presents centroid-invariant novel color gamut expansion method considering the optimal color as an ideal target and finally apply it to actual low-saturation images to verify its effect.","PeriodicalId":15924,"journal":{"name":"Journal of Imaging Science and Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135639313","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

The Exploration of Specific Associations from Words to Colours 从单词到颜色的特定联想的探索

IF 1 4区计算机科学

Journal of Imaging Science and Technology Pub Date : 2023-09-01 DOI: 10.2352/j.imagingsci.technol.2023.67.5.050401

Yun Chen, Jie Yang, Fan Zhang, Kaida Xiao, Stephen Westland

引用次数: 0

Locus Filters: Theory and Application 轨迹滤波器:理论与应用

4区计算机科学

Journal of Imaging Science and Technology Pub Date : 2023-09-01 DOI: 10.2352/j.imagingsci.technol.2023.67.5.050407

Rada Deeb, Graham D. Finlayson, Elaheh Daneshvar

引用次数: 0

Automotive Paint Defect Classification: Factory-Specific Data Generation using CG Software for Deep-Learning Models 汽车油漆缺陷分类:使用CG软件进行深度学习模型的工厂特定数据生成

4区计算机科学

Journal of Imaging Science and Technology Pub Date : 2023-09-01 DOI: 10.2352/j.imagingsci.technol.2023.67.5.050412

Kazuki Iwata, Haotong Guo, Ryuichi Yoshida, Yoshihito Souma, Chawan Koopipat, Masato Takahashi, Norimichi Tsumura

引用次数: 0

Multi-dimension and Multi-level Information Fusion for Facial Expression Recognition 面向面部表情识别的多维多层次信息融合

IF 1 4区计算机科学

Journal of Imaging Science and Technology Pub Date : 2023-07-01 DOI: 10.2352/j.imagingsci.technol.2023.67.4.040410

Mei Bie, Huan-Yu Xu, Quanle Liu, Yan Gao, Xiangjiu Che

引用次数: 0

An Intelligent Material Handling System for Hybrid Robot based on Visual Navigation 基于视觉导航的混合机器人智能物料搬运系统

IF 1 4区计算机科学

Journal of Imaging Science and Technology Pub Date : 2023-07-01 DOI: 10.2352/j.imagingsci.technol.2023.67.4.040409

Xiaorui Zhao, Xue-Fang Chen

引用次数: 0