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2009 16th International Conference on Digital Signal Processing最新文献

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Signal processing in dual domain by adaptive projected subgradient method 自适应投影亚梯度法对偶域信号处理
2009 16th International Conference on Digital Signal Processing Pub Date : 2009-07-05 DOI: 10.1109/ICDSP.2009.5201250
M. Yukawa, K. Slavakis, I. Yamada
{"title":"Signal processing in dual domain by adaptive projected subgradient method","authors":"M. Yukawa, K. Slavakis, I. Yamada","doi":"10.1109/ICDSP.2009.5201250","DOIUrl":"https://doi.org/10.1109/ICDSP.2009.5201250","url":null,"abstract":"The goal of this paper is to establish a novel signal processing paradigm that enables us to find a point meeting time-variable specifications in dual domain (e.g., time and frequency domains) simultaneously. For this purpose, we define a new problem which we call adaptive split feasibility problem (ASFP). In the ASFP formulation, we have (i) a priori knowledge based convex constraints in the Euclidean spaces ℝN and ℝM and (ii) data-dependent convex sets in ℝN and ℝM; the latter are obtained in a sequential fashion. Roughly speaking, the problem is to find a common point of all the sets defined on ℝN such that its image under a given linear transformation is a common point of all the sets defined on ℝM, if such a point exists. We prove that the adaptive projected subgradient method (APSM) deals with the ASFP by employing (i) a projected gradient operator with respect to (w.r.t.) a ‘fixed’ proximity function reflecting the convex constraints and (ii) a subgradient projection w.r.t. ‘time-varying’ objective functions reflecting the data-dependent sets. The resulting algorithm requires no unwanted operations such as matrix inversion, therefore it is suitable for real-time implementation. A convergence analysis is presented and verified by numerical examples.","PeriodicalId":409669,"journal":{"name":"2009 16th International Conference on Digital Signal Processing","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124905240","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: 4
Circular Spatial improved watermark embedding using a new Global SIFT synchronization scheme 基于全局SIFT同步的圆形空间水印嵌入改进算法
2009 16th International Conference on Digital Signal Processing Pub Date : 2009-07-05 DOI: 10.1109/ICDSP.2009.5201048
L. Verstrepen, T. Meesters, Tim Dams, A. Dooms, Dieter Bardyn
{"title":"Circular Spatial improved watermark embedding using a new Global SIFT synchronization scheme","authors":"L. Verstrepen, T. Meesters, Tim Dams, A. Dooms, Dieter Bardyn","doi":"10.1109/ICDSP.2009.5201048","DOIUrl":"https://doi.org/10.1109/ICDSP.2009.5201048","url":null,"abstract":"In image watermarking, many attacks will result in a synchronization problem between embedder and detector. A novel way to, partly, overcome this problem is embedding with feature points. In this paper we describe a synchronization system based on SIFT feature points. These points are characterized as being a localized feature containing semantic information of the image and can usually be retrieved after the image is attacked. We present an improvement on the work of Lee et al.[1], by using a more robust SIFT algorithm for feature point detection which we called Global SIFT (GLOS) and an adaptation of the Circular Spatial watermarking algorithm using so called mean QIM (CSI). We experimentally show an increase in detection rate and robustness of the watermarks after geometric attacks.","PeriodicalId":409669,"journal":{"name":"2009 16th International Conference on Digital Signal Processing","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124986840","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
Leveraging social media for training object detectors 利用社交媒体来训练目标探测器
2009 16th International Conference on Digital Signal Processing Pub Date : 2009-07-05 DOI: 10.1109/ICDSP.2009.5201113
E. Chatzilari, S. Nikolopoulos, Y. Kompatsiaris, Eirini Giannakidou, A. Vakali
{"title":"Leveraging social media for training object detectors","authors":"E. Chatzilari, S. Nikolopoulos, Y. Kompatsiaris, Eirini Giannakidou, A. Vakali","doi":"10.1109/ICDSP.2009.5201113","DOIUrl":"https://doi.org/10.1109/ICDSP.2009.5201113","url":null,"abstract":"The fact that most users tend to tag images emotionally rather than realistically makes social datasets inherently flawed from a computer vision perspective. On the other hand they can be particularly useful due to their social context and their potential to grow arbitrary big. Our work shows how a combination of techniques operating on both tag and visual information spaces, manages to leverage the associated weak annotations and produce region-detail training samples. In this direction we make some theoretical observations relating the robustness of the resulting models, the accuracy of the analysis algorithms and the amount of processed data. Experimental evaluation performed against manually trained object detectors reveals the strengths and weaknesses of our approach.","PeriodicalId":409669,"journal":{"name":"2009 16th International Conference on Digital Signal Processing","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114263053","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
Image forensics using generalised Benford's Law for accurate detection of unknown JPEG compression in watermarked images 图像取证使用广义本福德定律准确检测未知的JPEG压缩水印图像
2009 16th International Conference on Digital Signal Processing Pub Date : 2009-07-05 DOI: 10.1109/ICDSP.2009.5201261
Xi Zhao, A. Ho, Y. Shi
{"title":"Image forensics using generalised Benford's Law for accurate detection of unknown JPEG compression in watermarked images","authors":"Xi Zhao, A. Ho, Y. Shi","doi":"10.1109/ICDSP.2009.5201261","DOIUrl":"https://doi.org/10.1109/ICDSP.2009.5201261","url":null,"abstract":"In the past few years, semi-fragile watermarking has become increasingly important as it can be used to verify the content of images and to localise the tampered areas, while tolerating some non-malicious manipulations. In the literature, the majority of semi-fragile algorithms have applied a predetermined threshold to tolerate errors caused by JPEG compression. However, this predetermined threshold is typically fixed and cannot be easily adapted to different amounts of errors caused by unknown JPEG compression at different quality factors (QFs) applied to the watermarked images. In this paper, we analyse the relationship between QF and threshold, and propose the use of generalised Benford's Law as an image forensics technique for semi-fragile watermarking, to accurately detect the unknown QF of the images. The results obtained show an overall average QF correct detection rate of approximately 99% when 5% of the pixels are subjected to image content tampering, as well as compression using different QFs (ranging from 95 to 65). Consequently, our proposed image forensics method can adaptively adjust the threshold for images based on the estimated QF, therefore, improving the accuracy rates in authenticating and localising the tampered regions for semi-fragile watermarking.","PeriodicalId":409669,"journal":{"name":"2009 16th International Conference on Digital Signal Processing","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131109490","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
Variational 1D signal registration and shape geodesics for shape classification: Application to marine biological archives 形状分类的变分一维信号配准与形状测地线:在海洋生物档案中的应用
2009 16th International Conference on Digital Signal Processing Pub Date : 2009-07-05 DOI: 10.1109/ICDSP.2009.5201203
K. Nasreddine, A. Benzinou, V. Parisi-Baradad, Ronan Fablet
{"title":"Variational 1D signal registration and shape geodesics for shape classification: Application to marine biological archives","authors":"K. Nasreddine, A. Benzinou, V. Parisi-Baradad, Ronan Fablet","doi":"10.1109/ICDSP.2009.5201203","DOIUrl":"https://doi.org/10.1109/ICDSP.2009.5201203","url":null,"abstract":"When two 1D signals are compared, they must be represented in the same reference system. In most cases, biological signals present a big interindividual variability that should be eliminated in order to compare them properly. This variability can be erased by aligning the signals. A robust variational setting is proposed for 1D signal registration and applied to the computation of shape geodesics for shape classification issues. For validation purposes, experiments are carried out on real signals and shapes issued from marine biological archives which depict a high interindividual variability such that registration-based approaches are of particular interest.","PeriodicalId":409669,"journal":{"name":"2009 16th International Conference on Digital Signal Processing","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133509555","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
Extraction and selection of geoelectrical data features 地电数据特征提取与选择
2009 16th International Conference on Digital Signal Processing Pub Date : 2009-07-05 DOI: 10.1109/ICDSP.2009.5201192
A. Ifantis, Vasilis N. Nikolaidis
{"title":"Extraction and selection of geoelectrical data features","authors":"A. Ifantis, Vasilis N. Nikolaidis","doi":"10.1109/ICDSP.2009.5201192","DOIUrl":"https://doi.org/10.1109/ICDSP.2009.5201192","url":null,"abstract":"Extraction and selection of proper signal characteristics is a significant step affecting the success of any subsequent data analysis. We describe a process used to extract features from a 6-year, single-channel Long Term Geoelectric Potential difference (LTGP) signal, recorded in 1998–2003 at Western Greece. Features are extracted from consecutive segments of the signal, and evaluated to identify those possibly correlated with the seismic activity of the region. Evaluation is aided by pattern recognition techniques, and uses information from all seismic events of medium or larger magnitude occurring in the region. Initial results indicate that the approach may help reveal signal features whose properties deserve further investigation.","PeriodicalId":409669,"journal":{"name":"2009 16th International Conference on Digital Signal Processing","volume":"269 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131802970","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
Fast DCT-based algorithms for signal convolution and translation 基于dct的快速信号卷积和转换算法
2009 16th International Conference on Digital Signal Processing Pub Date : 2009-07-05 DOI: 10.1109/ICDSP.2009.5201263
Leonid Bilevich, L. Yaroslavsky
{"title":"Fast DCT-based algorithms for signal convolution and translation","authors":"Leonid Bilevich, L. Yaroslavsky","doi":"10.1109/ICDSP.2009.5201263","DOIUrl":"https://doi.org/10.1109/ICDSP.2009.5201263","url":null,"abstract":"Fast DCT-based algorithms are presented for signal convolution and translation that are virtually free of boundary effects, characteristic for corresponding DFT-based fast algorithms. The properties of DCT relevant to the subject are summarized and compared to the corresponding properties of DFT.","PeriodicalId":409669,"journal":{"name":"2009 16th International Conference on Digital Signal Processing","volume":"110 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115528846","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
Learning speech features in the presence of noise: Sparse convolutive robust non-negative matrix factorization 有噪声的语音特征学习:稀疏卷积鲁棒非负矩阵分解
2009 16th International Conference on Digital Signal Processing Pub Date : 2009-07-05 DOI: 10.1109/ICDSP.2009.5201068
R. Fréin, S. Rickard
{"title":"Learning speech features in the presence of noise: Sparse convolutive robust non-negative matrix factorization","authors":"R. Fréin, S. Rickard","doi":"10.1109/ICDSP.2009.5201068","DOIUrl":"https://doi.org/10.1109/ICDSP.2009.5201068","url":null,"abstract":"We introduce a non-negative matrix factorization technique which learns speech features with temporal extent in the presence of non-stationary noise. Our proposed technique, namely Sparse convolutive robust non-negative matrix factorization, is robust in the presence of noise due to our explicit treatment of noise as an interfering source in the factorization. We derive multiplicative update rules using the alpha divergence objective. We show that our proposed method yields superior performance to sparse convolutive non-negative matrix factorization in a feature learning task on noisy data and comparable results to dedicated speech enhancement techniques.","PeriodicalId":409669,"journal":{"name":"2009 16th International Conference on Digital Signal Processing","volume":"131 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114661941","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: 12
Estimating the probability fo false alarm for a zero-bit watermarking technique 零比特水印的虚警概率估计
2009 16th International Conference on Digital Signal Processing Pub Date : 2009-07-05 DOI: 10.1109/ICDSP.2009.5201130
T. Furon, Cyrille Jégourel, A. Guyader, F. Cérou
{"title":"Estimating the probability fo false alarm for a zero-bit watermarking technique","authors":"T. Furon, Cyrille Jégourel, A. Guyader, F. Cérou","doi":"10.1109/ICDSP.2009.5201130","DOIUrl":"https://doi.org/10.1109/ICDSP.2009.5201130","url":null,"abstract":"Assessing that a probability of false alarm is below a given significance level is a crucial issue in watermarking. We propose an iterative and self-adapting algorithm which estimates very low probabilities of error. Some experimental investigations validates its performance for a rare detection scenario where there exists a close form formula of the probability of false alarm. Our algorithm appears to be much quicker and more accurate than a classical Monte Carlo estimator. It even allows the experimental measurement of error exponents.","PeriodicalId":409669,"journal":{"name":"2009 16th International Conference on Digital Signal Processing","volume":"46 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114842590","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
Embedded Volterra for prediction of electromyographic signals during labour 在分娩过程中嵌入Volterra来预测肌电信号
2009 16th International Conference on Digital Signal Processing Pub Date : 2009-07-05 DOI: 10.1109/ICDSP.2009.5201137
W. Zgallai
{"title":"Embedded Volterra for prediction of electromyographic signals during labour","authors":"W. Zgallai","doi":"10.1109/ICDSP.2009.5201137","DOIUrl":"https://doi.org/10.1109/ICDSP.2009.5201137","url":null,"abstract":"It has been demonstrated that the dynamics of abdominal electromyographic signals (AEMG) during labour contractions are multi-fractal chaotic. A new embedded multi-step Volterra structure, which exploits the non-linear signal dynamics embedded in the attractor and integrates them in the design of such structures to gauge the long-term behaviour of the dynamics, has been introduced. The long-term predictive capability of the structure is tested by using a closed-loop adaptation scheme without any external input signal applied to the structure. Evidence of long-term prediction of highly complex labour contraction signals using only a small fraction of this sample is provided. In this paper, the Non-linear Auto-Regressive with exogenous inputs (NARX) Recurrent Neural Network (RNN) Multi-Layer Perceptron (MLP) model and the embedded cubic Volterra structure for the reconstruction of the underlying dynamics of labour contraction signals are compared.","PeriodicalId":409669,"journal":{"name":"2009 16th International Conference on Digital Signal Processing","volume":"581 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2009-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117066316","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
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