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2016 International Image Processing, Applications and Systems (IPAS)最新文献

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Efficient implementation of sobel filter based on GPUs cards 基于gpu卡的sobel滤波器的高效实现
2016 International Image Processing, Applications and Systems (IPAS) Pub Date : 2016-11-01 DOI: 10.1109/IPAS.2016.7880126
Mouna Afif, Yahia Said, Haythem Bahri, Mohamed Atri
{"title":"Efficient implementation of sobel filter based on GPUs cards","authors":"Mouna Afif, Yahia Said, Haythem Bahri, Mohamed Atri","doi":"10.1109/IPAS.2016.7880126","DOIUrl":"https://doi.org/10.1109/IPAS.2016.7880126","url":null,"abstract":"The Graphics processors or GPUs have become in a few years powerful tools for applications that require a massively parallel computing. Currently include the applications in multimedia processing, the engineering science and image processing in real time. They offer many advantages such as acceleration of treatment and down energy consumption from an equivalent CPU power. In this paper, we will show the effectiveness of our approach sobel filter (features extraction) by parallelizing the processing applied to different images with different sizes.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115250378","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
Classification of epileptic cerebral activity using robust features and support vector machines 基于鲁棒特征和支持向量机的癫痫脑活动分类
2016 International Image Processing, Applications and Systems (IPAS) Pub Date : 2016-11-01 DOI: 10.1109/IPAS.2016.7880118
C. Mahjoub, S. Chaibi, Tarek Lajnef, A. Kachouri
{"title":"Classification of epileptic cerebral activity using robust features and support vector machines","authors":"C. Mahjoub, S. Chaibi, Tarek Lajnef, A. Kachouri","doi":"10.1109/IPAS.2016.7880118","DOIUrl":"https://doi.org/10.1109/IPAS.2016.7880118","url":null,"abstract":"Epileptic seizure detection requires the study of electroencephalogram (EEG) data. Visual marking of seizure onset in such EEG recordings is quite tedious, naturally subjective, extremely time consuming, and it may lead to inaccurate detection. Thus, the development of a robust framework for automatic seizure classification is necessary and can be very useful in epilepsy investigation. In this paper, a classical method has been improved. Our contribution includes the use of linear and non linear features which have been incorporated into the Support Vector Machines (SVM) classifier. Accordingly, the detection performance has been compared using both radial basis functions (RBF) and linear SVM kernels. Our main finding reveals that the system can correctly classify the EEG data with an average sensitivity of 99.68%, an average specificity of 99.81% and an average accuracy of 99.75%, while 100% of sensitivity, specificity and accuracy are also achieved in single-trial classification. A final comparison between the performance levels obtained with our method and those obtained with previous techniques is undertaken to prove the effectiveness of our method for seizure detection.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131925353","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: 3
Yawning detection by the analysis of variational descriptor for monitoring driver drowsiness 用变分描述子分析哈欠检测驾驶员困倦状态
2016 International Image Processing, Applications and Systems (IPAS) Pub Date : 2016-11-01 DOI: 10.1109/IPAS.2016.7880127
Belhassen Akrout, W. Mahdi
{"title":"Yawning detection by the analysis of variational descriptor for monitoring driver drowsiness","authors":"Belhassen Akrout, W. Mahdi","doi":"10.1109/IPAS.2016.7880127","DOIUrl":"https://doi.org/10.1109/IPAS.2016.7880127","url":null,"abstract":"The road safety is a problem which was approached by several countries following a big raise of the number of accidents. The drowsiness represents one among the causes of the road accidents. The accidents related to the drowsiness often occur on the highways, but also on the main roads, even inside the localities. Today, it is possible to detect the state of tiredness of the driver with the development of the technology of the computer vision. The results of research in physiology show that the first level of lack of vigilance appears by an increase in the frequency of the yawn. In this work, we propose a novel approach for yawning detection for monitoring driver fatigue. In fact, our approach rests on the study of the spatio-temporal descriptors of a nonstationary and non-linear signal. This approach is evaluated by both YawDD [1] and our MiraclHB [2] databases. The evaluation shows many promising results and shows the effectiveness of the suggested approach.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"15 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116729760","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: 29
Hidden conditional random fields for gait recognition 用于步态识别的隐藏条件随机场
2016 International Image Processing, Applications and Systems (IPAS) Pub Date : 2016-11-01 DOI: 10.1109/IPAS.2016.7880139
M. Hagui, M. Mahjoub
{"title":"Hidden conditional random fields for gait recognition","authors":"M. Hagui, M. Mahjoub","doi":"10.1109/IPAS.2016.7880139","DOIUrl":"https://doi.org/10.1109/IPAS.2016.7880139","url":null,"abstract":"Gait is a recent important research field among the computer vision community. It aims identifying humans by analyzing their walk. It has different advantage comparing to others biometrics technologies such as face recognition, iris recognition and fingerprint. It can be performed at distance and without subject cooperation. Also, it doesn't need high resolution of image. In this paper, we present a new discriminative method for gait recognition using hybrid conditional random fields (CRF). We use a Hidden CRF model to combine two classifiers; a spatial classifier which assigns a label to a local feature (SURF descriptors) and temporal classifier which uses a motion History Image (MHI). The proposed framework, firstly extracts the human silhouette. Secondly, it takes out spatial and temporal cues from each frame. Then, it applies the MLP classification to the two set of features to obtain the Hidden CRF input; the final step is recognizing person with HCRF. Experimental results showed the superiority of our proposed method over several state of arts.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"105 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122116469","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
An efficient technique for the extraction of microcalcification's severity features 一种提取微钙化严重程度特征的有效方法
2016 International Image Processing, Applications and Systems (IPAS) Pub Date : 2016-11-01 DOI: 10.1109/IPAS.2016.7880149
Mouna Zouari Mehdi, Norhene Gargouri Ben Ayed, Alima Damak Masmoudi, Dorra Sellemi
{"title":"An efficient technique for the extraction of microcalcification's severity features","authors":"Mouna Zouari Mehdi, Norhene Gargouri Ben Ayed, Alima Damak Masmoudi, Dorra Sellemi","doi":"10.1109/IPAS.2016.7880149","DOIUrl":"https://doi.org/10.1109/IPAS.2016.7880149","url":null,"abstract":"Microcalcifications are very tiny deposits of calcium allocated in the breast tissue. Their gray level is similar to the dense normal breast tissue so its very difficult to differentiate between them. Once detected, its very difficult to between malign end benign microcalcifications. In this paper, we apply a new method to extract features of microcalcifications in order to classify them into malign and benign. This technique, called the Discriminative Completed Local Binary Pattern (DisCLBP), extracts texture characteristics of breast tissue in order to characterize the severity of microcalcifications. Classification of these structures is accomplished through Artificial Neural Network (ANN), which separate them in two groups: malignant and benign microcalcifications. Performance results are given in terms of receiver operating characteristic (ROC). The area under curve (AUC) of the corresponding approach has been found to be 93.45%.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121946008","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
A comparative study of GOM, uLBP, VLC and fractional Eigenfaces for face recognition GOM、uLBP、VLC和分数特征人脸识别的比较研究
2016 International Image Processing, Applications and Systems (IPAS) Pub Date : 2016-11-01 DOI: 10.1109/IPAS.2016.7880143
Ahmed Ghorbel, Imen Tajouri, Walid Aydi, N. Masmoudi
{"title":"A comparative study of GOM, uLBP, VLC and fractional Eigenfaces for face recognition","authors":"Ahmed Ghorbel, Imen Tajouri, Walid Aydi, N. Masmoudi","doi":"10.1109/IPAS.2016.7880143","DOIUrl":"https://doi.org/10.1109/IPAS.2016.7880143","url":null,"abstract":"This paper compares four methods of feature extraction: Fractional Eigenfaces and Vander Lugt Correlator as global methods, and Gabor Ordinal Measures and Uniform Local Binary Pattern as local ones. We evaluate the four methods on the standard FERET probe data sets in order to study the robustness of these techniques against illumination variation, facial expression variation and aging. The Gabor ordinal measures as a combination of Gabor filters and ordinal measures outperforms the others methods on the four test sets in terms of recognition rate.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122489575","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
Administrative document segmentation based on texture approach and fuzzy clustering 基于纹理法和模糊聚类的行政文件分割
2016 International Image Processing, Applications and Systems (IPAS) Pub Date : 2016-11-01 DOI: 10.1109/IPAS.2016.7880128
Wala Zaaboub, Lotfi Tlig, M. Sayadi
{"title":"Administrative document segmentation based on texture approach and fuzzy clustering","authors":"Wala Zaaboub, Lotfi Tlig, M. Sayadi","doi":"10.1109/IPAS.2016.7880128","DOIUrl":"https://doi.org/10.1109/IPAS.2016.7880128","url":null,"abstract":"The document image segmentation is an indispensable task in the document layout analysis system. This paper presents an accurate segmentation approach based on fuzzy classification for the administrative document image. The texture-based analysis works for this kind of document image are rare. And the research works on specific tasks are limited. Moreover, the texture-based segmentation methods are desired because they do not rely strongly on a priori knowledge surrounding the document. In addition, the robustness of these methods for degraded documents has been proven. For these purposes, the texture is explored in the analysis for our image type, using a fuzzy classification. The Fisher score determinate the most discriminative texture features for our segmentation: mean and variance. Our approach achieves encouraging and promising results for the detection of document zones: text, image and background. Qualitative and quantitative experiments are presented to determinate our approach performance.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"51 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116828511","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
DWT-DCT-SVD based hybrid lossy image compression technique 基于DWT-DCT-SVD的混合有损图像压缩技术
2016 International Image Processing, Applications and Systems (IPAS) Pub Date : 2016-11-01 DOI: 10.1109/IPAS.2016.7880068
A. M. G. Hnesh, H. Demirel
{"title":"DWT-DCT-SVD based hybrid lossy image compression technique","authors":"A. M. G. Hnesh, H. Demirel","doi":"10.1109/IPAS.2016.7880068","DOIUrl":"https://doi.org/10.1109/IPAS.2016.7880068","url":null,"abstract":"A new hybrid transform coding methodology for lossy image compression that integrates discrete wavelet transform, discrete cosine Transform and singular value decomposition methods is proposed. The proposed system has enhancements in both the compression ratio and the computational time. The results demonstrate the advantages of the proposed system in comparison to the previous discrete cosine transform and singular value decomposition systems, Improvements in both compression ratio and computational time have been reported.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122576400","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
Maximization of the power “UWB” signal by random method while respecting official constraints 在尊重官方约束的情况下，通过随机方法实现功率“超宽带”信号的最大化
2016 International Image Processing, Applications and Systems (IPAS) Pub Date : 2016-11-01 DOI: 10.1109/IPAS.2016.7880151
M. Ketata, M. Dhieb, G. B. Hmida, A. Loussert, H. Ghariani, M. Lahiani
{"title":"Maximization of the power “UWB” signal by random method while respecting official constraints","authors":"M. Ketata, M. Dhieb, G. B. Hmida, A. Loussert, H. Ghariani, M. Lahiani","doi":"10.1109/IPAS.2016.7880151","DOIUrl":"https://doi.org/10.1109/IPAS.2016.7880151","url":null,"abstract":"In this paper, we try to maximize the power of ultra-wideband signal “UWB” sent to the target without breaching the restriction limits of the Federal Communications Commission “FCC”. The signal is a series of monocycle Gaussian pulses, characterized by the frequency center “FC”, Pulse Repetition Interval “PRI”. And the amplitude “A”. Maximizing the signal power under the FCC constraints: get a PSD (Power Spectral Density) as close to the barrier −41.3 dB as possible in the frequency domain. The method of random variables can be used to determine the optimal characteristics of the signal. We will also impose 0,025 as a maximum ratio between the center frequency and the PRI to avoid overlap between pulses. This signal is used to be sent to the human body in order to detect heart beats. To see the waveform near the heart : Firstly, we modeled the human body as the consisting of four semi-infinite layers. These layers are characterized by their dielectric relative constant, thickness and electrical conductivity. Then, we use the Finite Difference Time Domain (FDTD) to model the UWB propagation channel. This method was an efficient tool to predict the distribution of electromagnetic field along the propagation channel.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123882944","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
Fabric defect detection using local homogeneity and morphological image processing 基于局部均匀性和形态学图像处理的织物缺陷检测
2016 International Image Processing, Applications and Systems (IPAS) Pub Date : 2016-11-01 DOI: 10.1109/IPAS.2016.7880062
A. Rebhi, S. Abid, F. Fnaiech
{"title":"Fabric defect detection using local homogeneity and morphological image processing","authors":"A. Rebhi, S. Abid, F. Fnaiech","doi":"10.1109/IPAS.2016.7880062","DOIUrl":"https://doi.org/10.1109/IPAS.2016.7880062","url":null,"abstract":"In this paper, a new fabric detect detection algorithm based on local homogeneity and mathematical morphology is presented. In a first step, the local homogeneity of each pixel is computed to construct a new homogeneity image denoted as (H-image). Then a classical histogram is computed for the H-image to choose an optimal thresholding value to produce a corresponding binary image, which will be used to extract the optimal size and the shape of the Structuring Element (SE) for mathematical morphology. In a second step, the image is subjected to a series of morphological operations with this SE to detect the possible existing fabric defect. Simulation results exhibit accurate defect detection with low false alarms.","PeriodicalId":283737,"journal":{"name":"2016 International Image Processing, Applications and Systems (IPAS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123884193","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: 20
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