发布求助
文献互助 智能选刊 最新文献

2016 6th European Workshop on Visual Information Processing (EUVIP)最新文献

筛选
英文 中文
Change detection in aerial images using a Kendall's TAU distance pattern correlation 使用肯德尔TAU距离模式相关的航空图像变化检测
2016 6th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2016-10-01 DOI: 10.1109/EUVIP.2016.7764604
M. S. Javadi, M. Dahl, M. Pettersson
{"title":"Change detection in aerial images using a Kendall's TAU distance pattern correlation","authors":"M. S. Javadi, M. Dahl, M. Pettersson","doi":"10.1109/EUVIP.2016.7764604","DOIUrl":"https://doi.org/10.1109/EUVIP.2016.7764604","url":null,"abstract":"Change detection in aerial images is the core of many remote sensing applications to analyze the dynamics of a wide area on the ground. In this paper, a remote sensing method is proposed based on viewpoint transformation and a modified Kendall rank correlation measure to detect changes in oblique aerial images. First, the different viewpoints of the aerial images are compromised and then, a local pattern descriptor based on Kendall rank correlation coefficient is introduced. A new distance measure referred to as Kendall's Tau-d (Tau distance) coefficient is presented to determine the changed regions. The developed system is applied on oblique aerial images with very low aspect angles that obtained using an unmanned aerial vehicle in two different days with drastic change in illumination and weather conditions. The experimental results indicate the robustness of the proposed method to variant illumination, shadows and multiple viewpoints for change detection in aerial images.","PeriodicalId":136980,"journal":{"name":"2016 6th European Workshop on Visual Information Processing (EUVIP)","volume":"43 30","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131501293","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: 5
Hierarchical classification of HEP-2 cell images using class-specific features 使用类特异性特征的HEP-2细胞图像的分层分类
2016 6th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2016-10-01 DOI: 10.1109/EUVIP.2016.7764585
Vibha Gupta, Krati Gupta, A. Bhavsar, A. Sao
{"title":"Hierarchical classification of HEP-2 cell images using class-specific features","authors":"Vibha Gupta, Krati Gupta, A. Bhavsar, A. Sao","doi":"10.1109/EUVIP.2016.7764585","DOIUrl":"https://doi.org/10.1109/EUVIP.2016.7764585","url":null,"abstract":"The paper proposes a class-specific feature assisted automatic classification approach of microscopic HEp-2 cell images. Unlike traditional methods our method highlights two important aspects: (1) the visual characteristics of classes to formulate class-specific image features and (2) the classification task is treated as hierarchical verification sub-tasks. Thus, the overall classification problem is modeled as a verification of each class, using its class-specific features. We have demonstrated that the proposed method yields a high classification rate utilizing simple and efficient features with only (20%) of the data for training. Additionally, we also experimentally analyze the crucial aspects, such as comparison with a traditional non-hierarchical framework and performance evaluation on low contrast images which is useful for early disease detection.","PeriodicalId":136980,"journal":{"name":"2016 6th European Workshop on Visual Information Processing (EUVIP)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115027776","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: 8
Hyperspectral images unmixing with rare signals 高光谱图像与稀有信号的分离
2016 6th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2016-10-01 DOI: 10.1109/EUVIP.2016.7764605
Sylvain Ravel, S. Bourennane, C. Fossati
{"title":"Hyperspectral images unmixing with rare signals","authors":"Sylvain Ravel, S. Bourennane, C. Fossati","doi":"10.1109/EUVIP.2016.7764605","DOIUrl":"https://doi.org/10.1109/EUVIP.2016.7764605","url":null,"abstract":"Pixels in hyperspectral images are a mixing of source signals. Hyperspectral unmixing is an important issue in image processing. In this paper we consider a linear mixing model. We address the unmixing issue when some \"rare\" source signals are only present in few mixed pixels. We propose a new method based on Non-negative Matrix Factorization (NMF) with known endmembers' number. This method first estimates the abundant source signals. Then it detects pixels which contain the rare signals. Finally it processes those pixels to estimate the rare signals.","PeriodicalId":136980,"journal":{"name":"2016 6th European Workshop on Visual Information Processing (EUVIP)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126980130","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: 2
Classification of positron emission tomography brain images using first and second derivative features 正电子发射断层扫描脑图像的一阶和二阶导数特征分类
2016 6th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2016-10-01 DOI: 10.1109/EUVIP.2016.7764598
Imene Garali, M. Adel, S. Bourennane, E. Guedj
{"title":"Classification of positron emission tomography brain images using first and second derivative features","authors":"Imene Garali, M. Adel, S. Bourennane, E. Guedj","doi":"10.1109/EUVIP.2016.7764598","DOIUrl":"https://doi.org/10.1109/EUVIP.2016.7764598","url":null,"abstract":"Computer-Aided Diagnosis (CAD) for Positron Emission Tomography (PET) brain images is of importance for better quantifying and diagnosing neurodegenerative diseases like Alzheimer Disease (AD). This paper presents new features based on first and second derivatives, computed on brain PET images and aiming at better image classification in the case of AD. Brain images are first segmented into Volumes Of Interest (VOIs) using an atlas. To quantify the ability of features to separate AD from Healthy Control (HC), the orientation field for each VOI is studied. First, 3D gradient images are computed. First and second derivatives over each VOI is then computed. Inputting the mean, then the first and second derivatives features within VOIs into a Support Vector Machine (SVM) classifier, yields better classification accuracy rate than when inputting only the mean value as a feature.","PeriodicalId":136980,"journal":{"name":"2016 6th European Workshop on Visual Information Processing (EUVIP)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114505258","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: 2
On the robustness of action recognition methods in compressed and pixel domain 压缩域和像素域动作识别方法的鲁棒性研究
2016 6th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2016-10-01 DOI: 10.1109/EUVIP.2016.7764584
Vignesh Srinivasan, Serhan Gul, S. Bosse, Jan Timo Meyer, T. Schierl, C. Hellge, W. Samek
{"title":"On the robustness of action recognition methods in compressed and pixel domain","authors":"Vignesh Srinivasan, Serhan Gul, S. Bosse, Jan Timo Meyer, T. Schierl, C. Hellge, W. Samek","doi":"10.1109/EUVIP.2016.7764584","DOIUrl":"https://doi.org/10.1109/EUVIP.2016.7764584","url":null,"abstract":"This paper investigates the robustness of two state-of-the-art action recognition algorithms: a pixel domain approach based on 3D convolutional neural networks (C3D) and a compressed domain approach requiring only partial decoding of the video, based on feature description using motion vectors and Fisher vector encoding (MV-FV). We study the robustness of the two algorithms against: (i) quality variations, (ii) changes in video encoding scheme, (iii) changes in resolutions. Experiments are performed on the HMDB51 dataset. Our main findings are that C3D is robust to variations of these parameters while the MV-FV is very sensitive. Hence, we consider C3D as a baseline method for our analysis. We also analyze the reasons behind these different behaviors and discuss their practical implications.","PeriodicalId":136980,"journal":{"name":"2016 6th European Workshop on Visual Information Processing (EUVIP)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115294074","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: 5
Automatic lossy compression of noisy images by spiht or jpeg2000 in optimal operation point neighborhood 采用spiht或jpeg2000在最优工作点邻域下对噪声图像进行自动有损压缩
2016 6th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2016-10-01 DOI: 10.1109/EUVIP.2016.7764581
V. Lukin, A. Zemliachenko, S. Abramov, B. Vozel, K. Chehdi
{"title":"Automatic lossy compression of noisy images by spiht or jpeg2000 in optimal operation point neighborhood","authors":"V. Lukin, A. Zemliachenko, S. Abramov, B. Vozel, K. Chehdi","doi":"10.1109/EUVIP.2016.7764581","DOIUrl":"https://doi.org/10.1109/EUVIP.2016.7764581","url":null,"abstract":"It is often needed to compress images with providing certain properties or quality. Wavelet based coders SPIHT and JPEG2000 easily produce a desired compression ratio but not quality especially if one deals with compressing images corrupted by noise for which specific behavior of quality metrics on compression ratio (CR) or bpp might be observed. In particular, optimal operation point (OOP) where a metric determined for compressed and noise free images might have optimum can take place. Lossy compression in OOP or its neighborhood has several advantages, However, for its attaining for such wavelet based coders as SPIHT or JPEG2000, only iterative procedures that can be rather time consuming have been proposed so far. Here, we propose a single-step procedure for determining bpp to be set for providing compression in OOP neighborhood. This procedure exploits two features. First, rate/distortion curves for SPIHT and JPEG2000 are shown to be very similar to those ones for DCT-based coder AGU. Second, a fast and simple procedure for predicting compression ratio in OOP neighborhood (without image compressing) has been proposed for the coder AGU recently. Examples demonstrating that the proposed procedure performs accurately enough are given.","PeriodicalId":136980,"journal":{"name":"2016 6th European Workshop on Visual Information Processing (EUVIP)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114826140","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: 5
Visual salient sift keypoints descriptors for automatic target recognition 用于目标自动识别的视觉显著性sift关键点描述符
2016 6th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2016-10-01 DOI: 10.1109/EUVIP.2016.7764596
Ayoub Karine, A. Toumi, A. Khenchaf, M. Hassouni
{"title":"Visual salient sift keypoints descriptors for automatic target recognition","authors":"Ayoub Karine, A. Toumi, A. Khenchaf, M. Hassouni","doi":"10.1109/EUVIP.2016.7764596","DOIUrl":"https://doi.org/10.1109/EUVIP.2016.7764596","url":null,"abstract":"This paper addresses the problem of automatic target recognition (ATR) using inverse synthetic aperture radar (ISAR) images. In this context, we propose a novel approach for feature extraction to describe precisely an aircraft target from ISAR images. In our approach, a visual attention model is adopted to separate the salient regions from the background. After that, the scale invariant feature transform (SIFT) method is used to extract the keypoints and their descriptors. Then, a local salient feature is built by considering only the keypoints located in the salient region. For the classification step, the support vector machines (SVM) classifier is adopted. To validate the proposed approach, ISAR images database which was collected from anechoic chamber is used.","PeriodicalId":136980,"journal":{"name":"2016 6th European Workshop on Visual Information Processing (EUVIP)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127504376","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: 5
Improving skin lesion segmentation in dermoscopic images by thin artefacts removal methods 利用薄伪影去除方法改善皮肤镜图像中皮肤病变的分割
2016 6th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2016-10-01 DOI: 10.1109/EUVIP.2016.7764580
Tomás Majtner, Kristína Lidayová, Sule YAYILGAN YILDIRIM, J. Hardeberg
{"title":"Improving skin lesion segmentation in dermoscopic images by thin artefacts removal methods","authors":"Tomás Majtner, Kristína Lidayová, Sule YAYILGAN YILDIRIM, J. Hardeberg","doi":"10.1109/EUVIP.2016.7764580","DOIUrl":"https://doi.org/10.1109/EUVIP.2016.7764580","url":null,"abstract":"In dermoscopic images, various thin artefacts naturally appear, most usually in the form of hairs. While trying to find the border of the skin lesion, these artefacts effect the lesion segmentation methods and also the subsequent classification. Currently, there is a lot of research focus in this area and various methods are presented both for skin lesion segmentation and thin artefacts removal. In this paper, we investigate into three different thin artefacts removal methods and compare their results using two different skin lesion segmentation methods. The segmentation results are compared with ground truth segmentation. In addition, we introduce our novel artefacts removal method, which combined with the Expectation Maximization image segmentation outperforms all the tested methods.","PeriodicalId":136980,"journal":{"name":"2016 6th European Workshop on Visual Information Processing (EUVIP)","volume":"264 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117167560","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: 15
Unmixing improvement based on bootstrap for hyperspectral imagery 基于自举法的高光谱图像解混改进
2016 6th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2016-10-01 DOI: 10.1109/EUVIP.2016.7764606
C. Fossati, S. Bourennane, A. Cailly
{"title":"Unmixing improvement based on bootstrap for hyperspectral imagery","authors":"C. Fossati, S. Bourennane, A. Cailly","doi":"10.1109/EUVIP.2016.7764606","DOIUrl":"https://doi.org/10.1109/EUVIP.2016.7764606","url":null,"abstract":"This paper presents an unmixing method for hyperspectral data containing small targets. Each pixel of the target represent the useful data embedded among a large number of background pixels. With recent technological developments of hyperspectral sensors, the spatial resolution increases, and it is possible to detect some small targets containing few pixels. We propose in this paper a new approach based on bootstrap resampling method adapted to the linear mixing model which leads to artificially increase the abundance of useful pixels corresponding to the small targets . Then, we use the non-negative matrix factorization (NMF) with these resampled data to estimate the spectra of the targets. The experimental results based on synthetic and real images demonstrate the efficiency of this new approach for the unmixing of smallscale data such as small objects in hyperspectral images.","PeriodicalId":136980,"journal":{"name":"2016 6th European Workshop on Visual Information Processing (EUVIP)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127861893","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: 2
On the selection of residual formula for HDR video coding HDR视频编码残差公式的选择
2016 6th European Workshop on Visual Information Processing (EUVIP) Pub Date : 2016-10-01 DOI: 10.1109/EUVIP.2016.7764590
I. Bouzidi, A. O. Zaid, M. Larabi
{"title":"On the selection of residual formula for HDR video coding","authors":"I. Bouzidi, A. O. Zaid, M. Larabi","doi":"10.1109/EUVIP.2016.7764590","DOIUrl":"https://doi.org/10.1109/EUVIP.2016.7764590","url":null,"abstract":"High Dynamic Range (HDR) videos are commonly compressed using existing Low Dynamic Range (LDR) coding standards. This necessarily implies a Tone Mapping (TM) stage which aims at reducing the input video range while preserving the most significant scene details. In most cases, a residual sequence is encoded and used at the decoder side to recover the HDR content. The challenge is to efficiently encode both LDR sequences (TM and residual) without compromising the quality of the reconstructed video. Furthermore, the choice of the residual sequence can have an important impact on the HDR video coder performances. In this work, we aim to study and analyse different approaches for residual determination. The performance is discussed in terms of entropy of the residual and video coding. Objective assessments show that differential residual presents much higher efficiency than ratio residuals in terms of bandwidth saving and HDR reconstruction quality.","PeriodicalId":136980,"journal":{"name":"2016 6th European Workshop on Visual Information Processing (EUVIP)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122321762","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: 1
首页 上一页 下一页 尾页
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整，为了账户安全，请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们：info@booksci.cn Book学术提供免费学术资源搜索服务，方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号：604180095
Book学术官方微信