Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013最新文献_第3页

Exploring contour and texture features for context-aware patch-based inpainting 探索轮廓和纹理特征的上下文感知补丁为基础的绘画

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644932

Tijana Ruzic, A. Pižurica, W. Philips

{"title":"Exploring contour and texture features for context-aware patch-based inpainting","authors":"Tijana Ruzic, A. Pižurica, W. Philips","doi":"10.1109/STSIVA.2013.6644932","DOIUrl":"https://doi.org/10.1109/STSIVA.2013.6644932","url":null,"abstract":"In this paper, we explore the use of contour and texture features for context-aware patch-based image inpainting. Both of these features are obtained by analysing the image filtered with the bank of filters at multiple orientations and scales, specifically Gabor filters. We use contour features to define a novel patch priority, which represents the main contribution of this paper. The priority is used to determine the filling order of the missing region, which is crucial for the success of the algorithm. Our goal is to make better differentiation between patches with structured, textured and smooth content than related definitions. We employ this novel priority within our recently proposed context-aware inpainting method, which uses contextual descriptors to find contextually similar image regions to which the search for well matching replacement patches is constrained. Here we use texture features, together with color features, as contextual descriptors of image regions. The benefit of the context-aware approach is twofold: the chance of choosing wrong matches is reduced and the search for candidate patches is accelerated. Experimental results demonstrate the benefit of the proposed method compared to state-of-the-art.","PeriodicalId":359994,"journal":{"name":"Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134053409","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

Evaluation of nine bioinformatic platforms using a viral model for RNA secondary structure prediction 利用病毒模型评价RNA二级结构预测的九个生物信息学平台

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644925

Luisa Fernanda Restrepo Rodriguez, F. Cortés-Mancera

{"title":"Evaluation of nine bioinformatic platforms using a viral model for RNA secondary structure prediction","authors":"Luisa Fernanda Restrepo Rodriguez, F. Cortés-Mancera","doi":"10.1109/STSIVA.2013.6644925","DOIUrl":"https://doi.org/10.1109/STSIVA.2013.6644925","url":null,"abstract":"RNA secondary (2D) structures are essential for cellular processes including protein translation; indeed some RNA viral pathogens use this strategy during replication cycle. Among Flaviviridae family, Hepatitis C Virus (HCV) presents a well experimentally-characterized secondary structure called IRES (Internal Ribosome Entry Site), which could be used as a Viral model for evaluating the accuracy RNA 2D structure in silico tools; the choice of free-available platforms is a principal concern because standard approaches for single-sequence RNA secondary structure prediction are dissimilar, training their parameters with known RNA structures that do not always include viral sequences. Here, we assessed the accuracy of nine web servers using the HCV IRES domain II. The platforms used were classified in three categories according to S and PPV values obtained. The lowest values were observed with IPKNOT 1.2.1 (NUPACK), Kinefold, VsFold 5.23 and CentroidHomfold, while IPKNOT 1.2.1 (CONTRAfold), IPKNOT 1.2.1 (McCaskill) and ContextFold 1.2.1 had acceptable computing output. Finally, MFOLD and RNAfold based on thermodynamic, RNAstructure (MaxExpect) and CentroidFold based on statistical weights, showed the highest accuracy with a similar topology to the expected structure, although these tools did not predict correctly all base-pairings. Further modifications in these platforms will be necessary to improve the RNA 2D structure prediction in viral models and others with higher RNA topology complexities.","PeriodicalId":359994,"journal":{"name":"Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130940024","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

Surface EMG signal analysis based on the empirical mode decomposition for human-robot interaction 基于经验模态分解的人机交互表肌电信号分析

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644943

A. F. Ruiz-Olaya, A. López-Delis

{"title":"Surface EMG signal analysis based on the empirical mode decomposition for human-robot interaction","authors":"A. F. Ruiz-Olaya, A. López-Delis","doi":"10.1109/STSIVA.2013.6644943","DOIUrl":"https://doi.org/10.1109/STSIVA.2013.6644943","url":null,"abstract":"Surface Electromyography (SEMG) is the electrical manifestation of the neuromuscular activation associated with a contracting muscle. SEMG directly reflects the human motion intention; thus, they can be used as input information for human-robot interaction. Taking into account that SEMG signals are complex physiological signals, being nonlinear, non-stationary and non-periodic, myoelectric classification methods must take into account such characteristics to be more effective. Recently, a novel technique for analysis of nonlinear and non-stationary signals was successfully applied to several kinds of investigations including seismological and biological signals. This technique, named Hilbert-Huang Transform (HHT) is formed by two complementary tools, which are called empirical mode decomposition (EMD) and Hilbert spectrum (HS). This work proposes a novel EMD-based myoelectric pattern recognition technique to be applied in human-robot interaction. The process of feature extraction is performed by two steps, firstly, the EMD decomposes the input SEMG signal into a set of functions designated as Intrinsic Mode Function (IMF); and secondly, it is calculated for each resulting IMF the RMS (Root Mean Square) and the coefficients of a four-order autoregressive model. The process of classification based on a linear classifier (Linear Discriminant Analysis). Using a database of EMG signals, the proposed method was applied to classify human upper-limb motion via EMG signals. The database includes 8 recorded SEMG channels from forearm in the execution of 7 movements. The error of classification was 3.3%. Obtained results suggest that the proposed myoelectric pattern recognition technique may be applied in Human-Robot Interaction (HRI) to control external systems such an upper limb motor neuroprosthesis.","PeriodicalId":359994,"journal":{"name":"Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013","volume":"44 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133107608","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

Image representation of flames from data processing of an optical multichannel analyzer spectrometer 光学多通道分析光谱仪数据处理火焰图像表示

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644906

D. Alviso, M. Mendieta, Jorge Molina, J. Rolón

引用次数: 0

Signal processing and waves graphing acceleration using FPGA 基于FPGA的信号处理和波形加速

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644924

Holguer A. Becerra, Jose P. Pinilla

引用次数: 1

Characterization of EEG signals using wavelet transform for motor imagination tasks in BCI systems 脑机接口系统运动想象任务脑电信号的小波变换表征

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644931

Boris Medina-Salgado, L. Duque-Muñoz, H. Fandiño-Toro

{"title":"Characterization of EEG signals using wavelet transform for motor imagination tasks in BCI systems","authors":"Boris Medina-Salgado, L. Duque-Muñoz, H. Fandiño-Toro","doi":"10.1109/STSIVA.2013.6644931","DOIUrl":"https://doi.org/10.1109/STSIVA.2013.6644931","url":null,"abstract":"Brain Computer Interface (BCI) covers an area of special interest, mainly due to the research being conducted to control external devices via thought commands, generating solutions in both motor disability and speech. These applications require the use of signal processing in real time, to be used in devices that help people with this type of disabilities. This paper presents a methodology for feature extraction of electroencephalographic (EEG) signals in motor imagery task of both left and right hand, using the public database BCI Competition 2003. It has been used the wavelet transform for the signal decomposition in the spectral bands of interest (known as brain rhythms). The brain rhythms characterization was conducted through relative energy, variance and standard deviation of the wavelet coefficients. In addition, we conducted the relevance analysis through the fuzzy entropy algorithm, to find the most important features within the training set. We obtained a classification accuracy of up to 98.44% using K-NN and SVM algorithms. The classification results allow inferring that the methodology is appropriate for the recognition of imagination movements in people with motor disabilities and could generate solutions in applications of BCI systems.","PeriodicalId":359994,"journal":{"name":"Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123199749","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

An evaluation of NMF algorithm on human action video retrieval NMF算法在人体动作视频检索中的评价

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644926

F. Páez, Jorge A. Vanegas, F. González

引用次数: 4

Vibration analysis in gear damage: Mathematical modeling and experimental validation 齿轮损伤振动分析:数学建模与实验验证

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644911

B. J. A. Ruiz, J. L. Lopez Lopez, Hector Fabio Quintero Riaza

引用次数: 4

Design and implementation of an embedded system for real time analysis of speech from people with Parkinson's disease 一个嵌入式系统的设计与实现，用于实时分析帕金森病患者的语音

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644913

J. C. Vásquez-Correa, J. Orozco-Arroyave, J. D. Arias-Londoño, J. Vargas-Bonilla, E. Noth

{"title":"Design and implementation of an embedded system for real time analysis of speech from people with Parkinson's disease","authors":"J. C. Vásquez-Correa, J. Orozco-Arroyave, J. D. Arias-Londoño, J. Vargas-Bonilla, E. Noth","doi":"10.1109/STSIVA.2013.6644913","DOIUrl":"https://doi.org/10.1109/STSIVA.2013.6644913","url":null,"abstract":"Parkinsons disease (PD) is a neurodegenerative disorder that affects the coordination and regulation of muscles and limbs, including those responsible of speech production, resulting alterations in voice intelligibility. It is already demonstrated that the constant speech therapy can improve the communication skills of the patients; however, it is required the development of flexible tools able to assess and guide the speech therapy of the patients without the intervention of the experts. In this paper one embedded system for the real time analysis of speech from people with Parkinson's disease is presented. Two platforms are developed. First, a Matlab Graphical User Interface is presented; second, the application is deployed in a minicomputer that has an audio codec, storage capacity and a efficient processing unit. The device has been equipped with an LCD monitor to display the information on real time, and a mini keyboard for the interface with the user. Different measurements that are commonly used in the assessment of speech from people with PD are evaluated. In agreement with the state of the art, an increment of the pitch variation is showed for patients with PD, additionally, lower values of the vowel space area (VSA) are also shown for speech recordings uttered by people with PD.","PeriodicalId":359994,"journal":{"name":"Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130339967","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

Optic disk detection and segmentation of retinal images using an evolution strategy on GPU 基于GPU进化策略的视盘检测与视网膜图像分割

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644904

German Sanchez Torres, J. Taborda

引用次数: 8