Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013最新文献_第2页

Video stabilization taken with a snake robot 用蛇机器人拍摄的视频稳定

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644937

J. Flórez, F. Calderon, C. Parra

引用次数: 7

Dynamic obstacle avoidance of a mobile robot through the use of machine vision algorithms 利用机器视觉算法实现移动机器人的动态避障

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644903

F. Espinosa, M. Robinson Jimenez, Luis Ruiz Cardenas, Juan Camilo Aponte

引用次数: 6

Epilepsy activity detection based on optimized one-class classifiers 基于优化单类分类器的癫痫活动检测

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644936

C. A. Aguirre-Echeverry, L. Duque-Muñoz, G. Castellanos-Domínguez

{"title":"Epilepsy activity detection based on optimized one-class classifiers","authors":"C. A. Aguirre-Echeverry, L. Duque-Muñoz, G. Castellanos-Domínguez","doi":"10.1109/STSIVA.2013.6644936","DOIUrl":"https://doi.org/10.1109/STSIVA.2013.6644936","url":null,"abstract":"Epilepsy represents a significant problem which reflects the existence of abnormal and hyper-synchronous discharges in large ensembles of neurons in brain structures. Despite, the epilepsy have been widely studied, its detection in incipient states is still in development. In order to solve this problem using EEG signals, a rigorous classification process have to be made. One-class classifiers are employed due their high performance under unbalanced classes and the lack of available target data from the biosignals but there are several aspects to consider like kernel parameter and the rejection rate parameter related with computational cost and performarce-stability respectively. In this paper it is proposed a methodology to improve the performance of a classification system using a optimized one-class classifer by means authomatic tuning algorithms. The Support vector data descriptor and mixture of Gaussians are used, and their performance and stability are compared, in order to determine the best one-class classifier. To increase the performance, stability and convergency time of the classifiers, the free parameters are optimized by particle swarm optimization(PSO). Using this approach, the sensitivity and specificity have been improve over the 95%. The methodology is tested with a database that correspond to 29 patients with medically intractable focal epilepsies. They were recorded by the Department of Epileptology of the University of Bonn, by means of intracranially implanted electrodes. It provides a new approach in epilepsy detection using EEG signals.","PeriodicalId":359994,"journal":{"name":"Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013","volume":"38 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":"133104895","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

Compressing audio signals with the use of the wavelet transform and Embedded Systems 利用小波变换和嵌入式系统压缩音频信号

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644947

Marcelo Herrera Martínez, Nelson Felipe Rosas, Carlos Camargo

引用次数: 0

Coded aperture compressive spectral imaging 编码孔径压缩光谱成像

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644909

Henry Arguello Fuentes, G. Arce

引用次数: 2

Automatic detection of bruises in fruit using Biospeckle techniques 利用生物斑点技术自动检测水果中的瘀伤

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644916

F. Vega, M. C. Torres

{"title":"Automatic detection of bruises in fruit using Biospeckle techniques","authors":"F. Vega, M. C. Torres","doi":"10.1109/STSIVA.2013.6644916","DOIUrl":"https://doi.org/10.1109/STSIVA.2013.6644916","url":null,"abstract":"This paper present a automatic analysis spatial-temporal speckle correlation technique applied for the bruises detection of different Colombian fruits namely apple and pear for the first time. The method is non-invasive, non-destructive and noncontact and is based on the study of variations in Biospeckle activities in short time data acquisition. The mount consist the 10mw LASER He-Ne 633nm as coherent light source, a diffuser, a USB camera, a control circuit of movement and stepper motor. Physical phenomena present absorption, scattering and interference. Temporal and spatial changes of subjective speckle pattern of the fruit have been measured in thirty samples each two seconds for a total analysis time of one minute. Using the above technique the cross-correlation coefficients of speckle pattern have been calculated. The cross-correlation coefficient change subject to the bruising in section fruit. Significant changes of cross-correlation coefficient values were observed in struck sections of fruit regard to sections not struck from the same. This work concluded that variance the cross-correlation coefficient is higher in struck sections of fruit regard to sections not struck from the same, that rapid analysis of samples in short time data acquisition can be used for quality control in fruit, impact detection not appreciated by visual inspection and others.","PeriodicalId":359994,"journal":{"name":"Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013","volume":"16 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":"126190955","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: 10

Visualizing multimodal image collections 可视化多模态图像集合

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644945

Anyela M. Chavarro, Jorge E. Camargo, F. González

引用次数: 1

Spectral selectivity in compressive spectral imaging based on grayscale coded apertures 基于灰度编码孔径压缩光谱成像中的光谱选择性

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644929

Ch. Hoover F. Rueda, G. Armando R. Calderon, Henry Arguello Fuentes

{"title":"Spectral selectivity in compressive spectral imaging based on grayscale coded apertures","authors":"Ch. Hoover F. Rueda, G. Armando R. Calderon, Henry Arguello Fuentes","doi":"10.1109/STSIVA.2013.6644929","DOIUrl":"https://doi.org/10.1109/STSIVA.2013.6644929","url":null,"abstract":"Compressive Spectral Imaging (CSI) is a signal acquisition technique that captures a spatial map of the spectral variation of a scene. Recently, a new optical imaging architecture called Coded Aperture Snapshot Spectral Imaging (CASSI) has emerged. The CASSI emulates the role of a spectrometer insomuch that it captures spectral information but uses coded apertures to take 2D compressed measurements from a 3D scene. Subsequently, an optimization algorithm is used to recover the full 3D spectral image from the measurements. However, in some applications is required to recover just a few selected set of spectral information. Then, compressive spectral selectivity aims to recover a specific set of spectral bands of interest. This work extends the capabilities of CASSI by replacing the traditional block-unblock coded apertures for a grayscale valued coded aperture. Further, the structures of the gray scale-valued coded apertures are designed such that a specific set of selected bands is reconstructed with high quality. A forward model and its corresponding reconstruction method are presented allowing to recover the desired bands, exclusively. Simulations are performed obtaining reconstructions exhibiting PSNRs of up to 30 dB.","PeriodicalId":359994,"journal":{"name":"Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013","volume":"27 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":"126304802","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

Access control system using palm of the hand image processing 门禁系统采用手掌图像处理

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644946

Robinson Jimenez Moreno, A. L. J. Alarcon, J. Ramírez, Carlos Andres Arredondo

引用次数: 1

Automatic detection of Parkinson's disease using noise measures of speech 使用语音噪声测量来自动检测帕金森病

Symposium of Signals, Images and Artificial Vision - 2013: STSIVA - 2013 Pub Date : 2013-10-24 DOI: 10.1109/STSIVA.2013.6644928

E. Belalcázar-Bolaños, J. Orozco-Arroyave, J. D. Arias-Londoño, J. Vargas-Bonilla, E. Nöth

{"title":"Automatic detection of Parkinson's disease using noise measures of speech","authors":"E. Belalcázar-Bolaños, J. Orozco-Arroyave, J. D. Arias-Londoño, J. Vargas-Bonilla, E. Nöth","doi":"10.1109/STSIVA.2013.6644928","DOIUrl":"https://doi.org/10.1109/STSIVA.2013.6644928","url":null,"abstract":"Parkinson's disease (PD) is a neurodegenerative disorder that is characterized by the loss of dopaminergic neurons in the mid brain. It is demonstrated that about 90% of the people with PD also develop speech impairments, exhibiting symptoms such as monotonic speech, low pitch intensity, inappropriate pauses, imprecision in consonants and problems in prosody; although they are already identify problems, only 3% to 4% of the patients receive speech therapy. The research community has addressed the problem of the automatic detection of PD by means of noise measures; however, in such works only the phonation of the English vowel /a/ has been considered. In this paper, the five Spanish vowels uttered by 50 people with PD and 50 healthy controls (HC) are evaluated automatically considering a set of four noise measures: Harmonics to Noise Ratio (HNR), Normalized Noise Energy (NNE), Cepstral HNR (CHNR) and Glottal to Noise Excitation Ratio (GNE). The decision on whether a speech recording is from a person with PD or from a HC is taken by a K nearest neighbors (k-NN) classifier, finding an accuracy of 66.57% when only the vowel /i/ is considered.","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":"114818195","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: 16