Pub Date : 2017-05-01DOI: 10.1109/ATSIP.2017.8075542
K. Baibai, Naoufal Elfakhouri, B. Bellach
This paper presents a new 3D information acquisition approach, which the aim is to reduce the amount of data to be processed in 3D shape recognition. This approach consists in extracting the 3D information from the deformations of the 2D lines projected on the 3D object, and transforms these deformations into a 1D signal. In order to simplify the extraction of descriptors of 3D shapes, the recognition process is consequently involved. In this framework, we developed a 3D acquisition system based on the projection of a multi-line pattern. We present in detail the different steps of the proposed approach, as well as the results obtained from each step. We describe the improvements we have made to 3D information acquisition processes.
{"title":"3D acquisition system for 3D forms recognition","authors":"K. Baibai, Naoufal Elfakhouri, B. Bellach","doi":"10.1109/ATSIP.2017.8075542","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075542","url":null,"abstract":"This paper presents a new 3D information acquisition approach, which the aim is to reduce the amount of data to be processed in 3D shape recognition. This approach consists in extracting the 3D information from the deformations of the 2D lines projected on the 3D object, and transforms these deformations into a 1D signal. In order to simplify the extraction of descriptors of 3D shapes, the recognition process is consequently involved. In this framework, we developed a 3D acquisition system based on the projection of a multi-line pattern. We present in detail the different steps of the proposed approach, as well as the results obtained from each step. We describe the improvements we have made to 3D information acquisition processes.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124372173","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}
Pub Date : 2017-05-01DOI: 10.1109/ATSIP.2017.8075595
Mohamed Lamine Bouibed, H. Nemmour, Y. Chibani
In this work, we propose a new descriptor that is called Gradient Local Binary Patterns (GLBP) for automatic keyword spotting in handwritten documents. GLBP is a gradient feature that improves the Histogram of Oriented Gradients (HOG) by calculating the gradient information at transitions of the Local Binary Pattern code. For the matching step, we use the Euclidian Distance and the Cosine Similarity. To show GLBP's performance, we used a Benchmark dataset which contains 100 documents written if 4 languages, from those documents 300 query were extracted to be spotted. The results obtained highlight the effectiveness of the proposed descriptor.
{"title":"New gradient descriptor for keyword spotting in handwritten documents","authors":"Mohamed Lamine Bouibed, H. Nemmour, Y. Chibani","doi":"10.1109/ATSIP.2017.8075595","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075595","url":null,"abstract":"In this work, we propose a new descriptor that is called Gradient Local Binary Patterns (GLBP) for automatic keyword spotting in handwritten documents. GLBP is a gradient feature that improves the Histogram of Oriented Gradients (HOG) by calculating the gradient information at transitions of the Local Binary Pattern code. For the matching step, we use the Euclidian Distance and the Cosine Similarity. To show GLBP's performance, we used a Benchmark dataset which contains 100 documents written if 4 languages, from those documents 300 query were extracted to be spotted. The results obtained highlight the effectiveness of the proposed descriptor.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"77 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132866642","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}
Pub Date : 2017-05-01DOI: 10.1109/ATSIP.2017.8075574
A. Bouakache, A. Tahraoui, R. Khedam, A. B. Aissa
In this paper, we present fusion and classification process of change indices using multitemporal satellites images in the aim to detect the change of surface states after a flood. This process is performed in the framework of Dempster Shafer Theory (DST), which takes into account the imprecision and the ignorance related to data. We apply this process to a study site located at south west of England, traversed by Severn river, which have undergone in October 2000 an important flood. For the detection of the flood damage, we have used two change indices: difference values and texture evolution. We find that change index fusion overcomes the limits of change mono-index classification.
{"title":"Change detection approach using evidential fusion of change indices","authors":"A. Bouakache, A. Tahraoui, R. Khedam, A. B. Aissa","doi":"10.1109/ATSIP.2017.8075574","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075574","url":null,"abstract":"In this paper, we present fusion and classification process of change indices using multitemporal satellites images in the aim to detect the change of surface states after a flood. This process is performed in the framework of Dempster Shafer Theory (DST), which takes into account the imprecision and the ignorance related to data. We apply this process to a study site located at south west of England, traversed by Severn river, which have undergone in October 2000 an important flood. For the detection of the flood damage, we have used two change indices: difference values and texture evolution. We find that change index fusion overcomes the limits of change mono-index classification.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114244875","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}
Pub Date : 2017-05-01DOI: 10.1109/ATSIP.2017.8075543
Bo Zhang, L. Siéler, Y. Morère, B. Bolmont, G. Bourhis
The QRS complex is the most significant segment in the Electrocardiography (ECG) signal. By detecting its position, we can learn the physiological informations of the subjects, e.g. heart rate. In this paper, we propose a FPGA architecture for QRS complex detection. The detection algorithm is based on Integer Haar Transform (IHT). Due to its integer nature, the IHT avoids the floating point calculations and thus can be easily implemented in FPGA. The FPGA Cyclone EP3C5F256C6 is used as the target chip and all the components of the system are implemented in VHSIC Hardware Description Language (VHDL). The testing results show that the proposed FPGA architecture can achieve an efficient detection performance where the total detection accuracy exceeds 98%. Meanwhile, the FPGA implementation shows good design efficiency in the term of silicon consumption. Only 8% silicon resources of the target chip are occupied. The proposed architecture will be adopted as a core unit to make a FPGA system for stress recognition given the heterogeneous data.
{"title":"Dedicated wavelet QRS complex detection for FPGA implementation","authors":"Bo Zhang, L. Siéler, Y. Morère, B. Bolmont, G. Bourhis","doi":"10.1109/ATSIP.2017.8075543","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075543","url":null,"abstract":"The QRS complex is the most significant segment in the Electrocardiography (ECG) signal. By detecting its position, we can learn the physiological informations of the subjects, e.g. heart rate. In this paper, we propose a FPGA architecture for QRS complex detection. The detection algorithm is based on Integer Haar Transform (IHT). Due to its integer nature, the IHT avoids the floating point calculations and thus can be easily implemented in FPGA. The FPGA Cyclone EP3C5F256C6 is used as the target chip and all the components of the system are implemented in VHSIC Hardware Description Language (VHDL). The testing results show that the proposed FPGA architecture can achieve an efficient detection performance where the total detection accuracy exceeds 98%. Meanwhile, the FPGA implementation shows good design efficiency in the term of silicon consumption. Only 8% silicon resources of the target chip are occupied. The proposed architecture will be adopted as a core unit to make a FPGA system for stress recognition given the heterogeneous data.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121707754","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}
Pub Date : 2017-05-01DOI: 10.1109/ATSIP.2017.8075515
I. Kallel, Sonda Ammar Bouhamed, Belhassen Akrout
An iris recognition requires parametric modeling texture. The extracted model should characterize the individual corresponding to considered iris. Such a model is often referred to as biometric signature. Several approaches to uniquely specify an iris by extracting parameters characteristic of its texture exist in the literature. An original approach based on an analysis by the Meyer wavelet of the iris texture is detailed in this paper. A comparative study between our approach and some techniques that have been studied, implemented and tested in subsequent work is carried out on the CASIA V.1 database. The experimental results show that the proposed method has promising performances.
{"title":"Clever use of Meyer wavelet for iris recognition","authors":"I. Kallel, Sonda Ammar Bouhamed, Belhassen Akrout","doi":"10.1109/ATSIP.2017.8075515","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075515","url":null,"abstract":"An iris recognition requires parametric modeling texture. The extracted model should characterize the individual corresponding to considered iris. Such a model is often referred to as biometric signature. Several approaches to uniquely specify an iris by extracting parameters characteristic of its texture exist in the literature. An original approach based on an analysis by the Meyer wavelet of the iris texture is detailed in this paper. A comparative study between our approach and some techniques that have been studied, implemented and tested in subsequent work is carried out on the CASIA V.1 database. The experimental results show that the proposed method has promising performances.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115355146","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}
Pub Date : 2017-05-01DOI: 10.1109/ATSIP.2017.8075556
N. B. Amor, Khaled Lahbib, T. Frikha
In this paper, we present a dynamically reconfigurable (DR) architecture for a 3D image synthesis application. We address different issues not covered in similar works especially the use of low complex and cost FPGA and the simultaneous support of different constraints like the energy consumption and the real time constraint. The proposed system uses an adaptation module that monitors the internal architecture modifications using FPGA dynamic reconfiguration mechanism.
{"title":"Design of a dynamically reconfigurable architecture for the 3D image synthesis","authors":"N. B. Amor, Khaled Lahbib, T. Frikha","doi":"10.1109/ATSIP.2017.8075556","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075556","url":null,"abstract":"In this paper, we present a dynamically reconfigurable (DR) architecture for a 3D image synthesis application. We address different issues not covered in similar works especially the use of low complex and cost FPGA and the simultaneous support of different constraints like the energy consumption and the real time constraint. The proposed system uses an adaptation module that monitors the internal architecture modifications using FPGA dynamic reconfiguration mechanism.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123711850","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}
Pub Date : 2017-05-01DOI: 10.1109/ATSIP.2017.8075607
Amine Brahmi, H. Ghennioui, C. Corbier, M. Lahbabi, F. Guillet
This work puts forward the problem of blind mixing matrix identification in the case of linearly mixed signals of cyclostationay sources whose cyclic frequencies are unknown and different. The identification is achieved using a semi-analytical solution. It takes advantage of the Eigenvalue Decomposition (EVD) of a set of algebraically particular matrices resulted from the application of the cyclic autocorrelation function on the mixed signals and rank-one selection criteria combined with a hierarchical clustering method. The proposed approach is applied to digital communication signals then numerical simulations are provided to illustrate the proper behaviour of the proposed method in different noise contexts.
{"title":"A semi-analytical method for blind separation of cyclostationary sources in digital communications","authors":"Amine Brahmi, H. Ghennioui, C. Corbier, M. Lahbabi, F. Guillet","doi":"10.1109/ATSIP.2017.8075607","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075607","url":null,"abstract":"This work puts forward the problem of blind mixing matrix identification in the case of linearly mixed signals of cyclostationay sources whose cyclic frequencies are unknown and different. The identification is achieved using a semi-analytical solution. It takes advantage of the Eigenvalue Decomposition (EVD) of a set of algebraically particular matrices resulted from the application of the cyclic autocorrelation function on the mixed signals and rank-one selection criteria combined with a hierarchical clustering method. The proposed approach is applied to digital communication signals then numerical simulations are provided to illustrate the proper behaviour of the proposed method in different noise contexts.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"157 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129593237","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}
Pub Date : 2017-05-01DOI: 10.1109/ATSIP.2017.8075553
Salwa Lagdali, M. Rziza
Higher order spectra are very useful in problems where either non Gaussianity, noise and non linearities are important. These properties are proved to be present in natural images. This yield higher order spectra and especially the third order, namely the bispectrum, to be an interesting tool in image processing. This paper presents higher order spectra in signal processing and their extension and applications to image processing, where the images are proved to be non Gaussian and non linear.
{"title":"Higher order spectra in image processing","authors":"Salwa Lagdali, M. Rziza","doi":"10.1109/ATSIP.2017.8075553","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075553","url":null,"abstract":"Higher order spectra are very useful in problems where either non Gaussianity, noise and non linearities are important. These properties are proved to be present in natural images. This yield higher order spectra and especially the third order, namely the bispectrum, to be an interesting tool in image processing. This paper presents higher order spectra in signal processing and their extension and applications to image processing, where the images are proved to be non Gaussian and non linear.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127269241","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}
Pub Date : 2017-05-01DOI: 10.1109/ATSIP.2017.8075535
Amine Amraoui, Y. Fakhri, M. A. Kerroum
The most emerging biometric technology used to ensure a reliable recognition rate is Multibiometrics. The unimodal recognition systems may lead to low recognition rate in real applications. To overcome this problem, we propose an approach for palmprint recognition based on local features. First, a palmprint image is divided into several sub-images, then the feature vectors are extracted from each sub-block by uniform local binary pattern. The feature vectors of all the sub-images are combined together to form the feature vector. Finally the pattern classification can be assured by using classifiers based on Euclidian distance and City-block. The effectiveness of proposed method has been verified on PolyU palmprint database. The experimental results show that the recognition rates are significantly improved compared with others methods existing in literature. The recognition rate of the proposed method is the highest among the other algorithms. The optimal recognition rate obtained is 99,4%. The experimental results have shown that unimodal system is effective.
{"title":"Unimodal palmprint recognition system based on local features","authors":"Amine Amraoui, Y. Fakhri, M. A. Kerroum","doi":"10.1109/ATSIP.2017.8075535","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075535","url":null,"abstract":"The most emerging biometric technology used to ensure a reliable recognition rate is Multibiometrics. The unimodal recognition systems may lead to low recognition rate in real applications. To overcome this problem, we propose an approach for palmprint recognition based on local features. First, a palmprint image is divided into several sub-images, then the feature vectors are extracted from each sub-block by uniform local binary pattern. The feature vectors of all the sub-images are combined together to form the feature vector. Finally the pattern classification can be assured by using classifiers based on Euclidian distance and City-block. The effectiveness of proposed method has been verified on PolyU palmprint database. The experimental results show that the recognition rates are significantly improved compared with others methods existing in literature. The recognition rate of the proposed method is the highest among the other algorithms. The optimal recognition rate obtained is 99,4%. The experimental results have shown that unimodal system is effective.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129170187","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}
Pub Date : 2017-05-01DOI: 10.1109/ATSIP.2017.8075608
Hala Alami Arroussi, ElMostafa Ziani, B. Bossoufi
In this paper, we present a double direct control of the torque of the doubly fed induction motor (DFIM). First, the modeling of the motor is carried out in order to apply the technique of dual direct control of the torque (DTC). Thereafter, an explanation of the said control is spread out as well as the principle of adjusting the flux and the electromagnetic torque according to the desired speed. Then, the estimation's method of these two control variables will be presented in addition to the adopted switching table of the hysteresis controllers used which is based on the model of the multi-level voltage inverter. Finally, the robustness of the developed system will be analyzed with a validation on the Matlab / Simulink environment to illustrate the performance of this command.
{"title":"Contribution to the enhancement of dual dtc application: Doubly fed induction motor","authors":"Hala Alami Arroussi, ElMostafa Ziani, B. Bossoufi","doi":"10.1109/ATSIP.2017.8075608","DOIUrl":"https://doi.org/10.1109/ATSIP.2017.8075608","url":null,"abstract":"In this paper, we present a double direct control of the torque of the doubly fed induction motor (DFIM). First, the modeling of the motor is carried out in order to apply the technique of dual direct control of the torque (DTC). Thereafter, an explanation of the said control is spread out as well as the principle of adjusting the flux and the electromagnetic torque according to the desired speed. Then, the estimation's method of these two control variables will be presented in addition to the adopted switching table of the hysteresis controllers used which is based on the model of the multi-level voltage inverter. Finally, the robustness of the developed system will be analyzed with a validation on the Matlab / Simulink environment to illustrate the performance of this command.","PeriodicalId":259951,"journal":{"name":"2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131231767","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}
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