Pub Date : 2008-12-01DOI: 10.1109/ISSPIT.2008.4775716
M. Zortea, A. Plaza
Hyperspectral imaging is a new technique in remote sensing which provides image data at hundreds of spectral wave-lengths, thus allowing a very detailed characterization of the surface of the Earth (from an airborne or satellite platform). One of the most important challenges in hyperspectral imaging is to find an adequate pool of pure signature spectra of the materials present in the scene. These pure signatures are then used to decompose the scene into a set of so-called abundance fractions by means of a spectral unmixing algorithm, thus allowing a detailed analysis of the scene with sub-pixel precision. Most techniques available in endmember extraction literature rely on exploiting the spectral properties of the data alone. As a result, the search for endmembers in a scene is often conducted by treating the data as a collection of spectral measurements with no spatial arrangement. In this paper, we propose a novel strategy to incorporate spatial information into the traditional spectral-based endmember search process. Specifically, we propose to estimate, for each pixel vector in the scene, a scalar value which is used to weight the importance of the spectral information associated to each pixel in terms of its spatial context. The proposed methodology, which favours the selection of highly representative endmembers located in spatially homogeneous areas, is shown in this work to significantly improve several spectral-based endmember extraction algorithms available in the literature.
{"title":"Improved Spectral Unmixing of Hyperspectral Images Using Spatially Homogeneous Endmembers","authors":"M. Zortea, A. Plaza","doi":"10.1109/ISSPIT.2008.4775716","DOIUrl":"https://doi.org/10.1109/ISSPIT.2008.4775716","url":null,"abstract":"Hyperspectral imaging is a new technique in remote sensing which provides image data at hundreds of spectral wave-lengths, thus allowing a very detailed characterization of the surface of the Earth (from an airborne or satellite platform). One of the most important challenges in hyperspectral imaging is to find an adequate pool of pure signature spectra of the materials present in the scene. These pure signatures are then used to decompose the scene into a set of so-called abundance fractions by means of a spectral unmixing algorithm, thus allowing a detailed analysis of the scene with sub-pixel precision. Most techniques available in endmember extraction literature rely on exploiting the spectral properties of the data alone. As a result, the search for endmembers in a scene is often conducted by treating the data as a collection of spectral measurements with no spatial arrangement. In this paper, we propose a novel strategy to incorporate spatial information into the traditional spectral-based endmember search process. Specifically, we propose to estimate, for each pixel vector in the scene, a scalar value which is used to weight the importance of the spectral information associated to each pixel in terms of its spatial context. The proposed methodology, which favours the selection of highly representative endmembers located in spatially homogeneous areas, is shown in this work to significantly improve several spectral-based endmember extraction algorithms available in the literature.","PeriodicalId":213756,"journal":{"name":"2008 IEEE International Symposium on Signal Processing and Information Technology","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117189489","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 : 2008-12-01DOI: 10.1109/ISSPIT.2008.4775647
E. Secerbegovic, M. Bolic, Z. Begic
The bandwidth broker is a management instance inside a PLC system, which has the complete overview about the network topology, the actual reserved bandwidth on each link inside its domain and should ideally have also a real-time view of the available bandwidth on each link. The bandwidth broker acts as an intermediate unit for call setups in a way that a call with ensured quality has to send a signaling packet to the broker which then manages each node taking part in this connection and reserves the bandwidth percentage and delay constraints necessary for the requested quality. The signaling between the routers and the bandwidth broker is at the moment very rudimental and consists of simple UDP packets containing a string with the desired quality.
{"title":"Advanced Bandwidth Brokering Architecture in PLC Networks","authors":"E. Secerbegovic, M. Bolic, Z. Begic","doi":"10.1109/ISSPIT.2008.4775647","DOIUrl":"https://doi.org/10.1109/ISSPIT.2008.4775647","url":null,"abstract":"The bandwidth broker is a management instance inside a PLC system, which has the complete overview about the network topology, the actual reserved bandwidth on each link inside its domain and should ideally have also a real-time view of the available bandwidth on each link. The bandwidth broker acts as an intermediate unit for call setups in a way that a call with ensured quality has to send a signaling packet to the broker which then manages each node taking part in this connection and reserves the bandwidth percentage and delay constraints necessary for the requested quality. The signaling between the routers and the bandwidth broker is at the moment very rudimental and consists of simple UDP packets containing a string with the desired quality.","PeriodicalId":213756,"journal":{"name":"2008 IEEE International Symposium on Signal Processing and Information Technology","volume":"152 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115792888","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 : 2008-12-01DOI: 10.1109/ISSPIT.2008.4775722
G. Reis, N. Fonseca, F. Fernández, A. Ferreira
This paper presents a genetic algorithm approach with harmonic structure evolution for polyphonic music transcription. Automatic music transcription is a very complex problem that continues waiting for solutions due to the harmonic complexity of musical sounds. More traditional approaches try to extract the information directly from the audio stream, but by taking into account that a polyphonic audio stream is no more than a combination of several musical notes, music transcription can be addressed as a search space problem where the goal is to find the sequence of notes that best models our audio signal. By taking advantage of the genetic algorithms to explore large search spaces we present a new approach to the music transcription problem. In order to reduce the harmonic overfitting several techniques were used including the encoding of the harmonic structure of the internal synthesizer inside the individual's genotype as a way to evolve towards the instrument played on the original audio signal. The results obtained in polyphonic piano transcriptions show the feasibility of the approach.
{"title":"A Genetic Algorithm Approach with Harmonic Structure Evolution for Polyphonic Music Transcription","authors":"G. Reis, N. Fonseca, F. Fernández, A. Ferreira","doi":"10.1109/ISSPIT.2008.4775722","DOIUrl":"https://doi.org/10.1109/ISSPIT.2008.4775722","url":null,"abstract":"This paper presents a genetic algorithm approach with harmonic structure evolution for polyphonic music transcription. Automatic music transcription is a very complex problem that continues waiting for solutions due to the harmonic complexity of musical sounds. More traditional approaches try to extract the information directly from the audio stream, but by taking into account that a polyphonic audio stream is no more than a combination of several musical notes, music transcription can be addressed as a search space problem where the goal is to find the sequence of notes that best models our audio signal. By taking advantage of the genetic algorithms to explore large search spaces we present a new approach to the music transcription problem. In order to reduce the harmonic overfitting several techniques were used including the encoding of the harmonic structure of the internal synthesizer inside the individual's genotype as a way to evolve towards the instrument played on the original audio signal. The results obtained in polyphonic piano transcriptions show the feasibility of the approach.","PeriodicalId":213756,"journal":{"name":"2008 IEEE International Symposium on Signal Processing and Information Technology","volume":"2017 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123982156","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 : 2008-12-01DOI: 10.1109/ISSPIT.2008.4775680
H. Do, Dooseop Choi, Hyuk Choi, Taejeong Kim
This paper presents a blind digital video watermarking scheme, which is especially robust to camcorder recording attacks and also to a variety of common video processing and geometric distortions. Using the fact that nearby frames of a video sequence are quite similar, the method embeds the watermark by temporal modulation of the frames. The watermark pattern used in modulation is generated based on the pixel-value histogram, which makes extraction free from geometric synchronization. To make it imperceptible, the watermark is adjusted according roughly to the Human Visual System. The experimental results demonstrate the robustness of the proposed method to camcorder recording attacks also involving geometric distortions and other video processing attacks such as MPEG and other compressions.
{"title":"Digital Video Watermarking Based on Histogram and Temporal Modulation and Robust to Camcorder Recording","authors":"H. Do, Dooseop Choi, Hyuk Choi, Taejeong Kim","doi":"10.1109/ISSPIT.2008.4775680","DOIUrl":"https://doi.org/10.1109/ISSPIT.2008.4775680","url":null,"abstract":"This paper presents a blind digital video watermarking scheme, which is especially robust to camcorder recording attacks and also to a variety of common video processing and geometric distortions. Using the fact that nearby frames of a video sequence are quite similar, the method embeds the watermark by temporal modulation of the frames. The watermark pattern used in modulation is generated based on the pixel-value histogram, which makes extraction free from geometric synchronization. To make it imperceptible, the watermark is adjusted according roughly to the Human Visual System. The experimental results demonstrate the robustness of the proposed method to camcorder recording attacks also involving geometric distortions and other video processing attacks such as MPEG and other compressions.","PeriodicalId":213756,"journal":{"name":"2008 IEEE International Symposium on Signal Processing and Information Technology","volume":"92 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124858752","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 : 2008-12-01DOI: 10.1109/ISSPIT.2008.4775725
F. Derraz, A. Taleb-Ahmed, A. Pinti, A. Chikh, F. Bereksi-Reguig
A new geometric active contour based level-sets model combining gradient, region and shape knowledge information cues is proposed to robust object detection boundaries in presence of occlusions and cluttered background. The gradient, region and shape knowledge information are incorporated as energy terms. The a priori shape model is based on statistical learning of the training data distribution where the structure of data distribution is approximated by a probability density model. The obtained probability is treated as Kernel Principal Component Analysis (KPC) by allowing the shapes that are close to the training data as energy term and incorporated a prior knowledge about shapes in a more robust manner into evolving equation model to constrain the further segmentation evolution process. We applied successfully the proposed model to synthetic and real MR images. The results drawn by the newer model are compared to expert segmentation and evaluated in terms of F-mesure.
{"title":"A Geometrical Active Contour Based on Statistical Shape Prior Model","authors":"F. Derraz, A. Taleb-Ahmed, A. Pinti, A. Chikh, F. Bereksi-Reguig","doi":"10.1109/ISSPIT.2008.4775725","DOIUrl":"https://doi.org/10.1109/ISSPIT.2008.4775725","url":null,"abstract":"A new geometric active contour based level-sets model combining gradient, region and shape knowledge information cues is proposed to robust object detection boundaries in presence of occlusions and cluttered background. The gradient, region and shape knowledge information are incorporated as energy terms. The a priori shape model is based on statistical learning of the training data distribution where the structure of data distribution is approximated by a probability density model. The obtained probability is treated as Kernel Principal Component Analysis (KPC) by allowing the shapes that are close to the training data as energy term and incorporated a prior knowledge about shapes in a more robust manner into evolving equation model to constrain the further segmentation evolution process. We applied successfully the proposed model to synthetic and real MR images. The results drawn by the newer model are compared to expert segmentation and evaluated in terms of F-mesure.","PeriodicalId":213756,"journal":{"name":"2008 IEEE International Symposium on Signal Processing and Information Technology","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121918367","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 : 2008-12-01DOI: 10.1109/ISSPIT.2008.4775696
Yuheng He, K. Hueske, Jurgen Gotze, E. Coersmeier
The efficient computation of joint direction-of-arrival (DOA) and frequency estimation from the data matrix obtained from a sensor array is discussed. High-resolution ESPRIT/MUSIC algorithms are used to compute the estimates. A preprocessing step uses a two-sided DFT (computed using FFT) and applies a threshold to generate a sparse matrix from the given data matrix. The Lanczos method is used to compute the SVD/EVD of the sparse matrix. This results in a reduced computational complexity if the complexity of the preprocessing step is small compared to the reduction of the computational effort obtained by exploiting the sparsity of the matrix. We also compare this procedure with the estimations based on one sensor and one snapshot of the sensor array, respectively. In this case we can build Hankel matrices from the data samples and apply ESPRIT/MUSIC methods to these Hankel matrices and these matrices after the preprocessing step, respectively. This also yields a reduced computational complexity (again using Lanczos' method) but decreases the accuracy of the estimates. We compare the computational effort and the mean square error (MSE) of the estimates for the different approaches.
{"title":"Efficient Computation of Joint Direction-Of-Arrival and Frequency Estimation","authors":"Yuheng He, K. Hueske, Jurgen Gotze, E. Coersmeier","doi":"10.1109/ISSPIT.2008.4775696","DOIUrl":"https://doi.org/10.1109/ISSPIT.2008.4775696","url":null,"abstract":"The efficient computation of joint direction-of-arrival (DOA) and frequency estimation from the data matrix obtained from a sensor array is discussed. High-resolution ESPRIT/MUSIC algorithms are used to compute the estimates. A preprocessing step uses a two-sided DFT (computed using FFT) and applies a threshold to generate a sparse matrix from the given data matrix. The Lanczos method is used to compute the SVD/EVD of the sparse matrix. This results in a reduced computational complexity if the complexity of the preprocessing step is small compared to the reduction of the computational effort obtained by exploiting the sparsity of the matrix. We also compare this procedure with the estimations based on one sensor and one snapshot of the sensor array, respectively. In this case we can build Hankel matrices from the data samples and apply ESPRIT/MUSIC methods to these Hankel matrices and these matrices after the preprocessing step, respectively. This also yields a reduced computational complexity (again using Lanczos' method) but decreases the accuracy of the estimates. We compare the computational effort and the mean square error (MSE) of the estimates for the different approaches.","PeriodicalId":213756,"journal":{"name":"2008 IEEE International Symposium on Signal Processing and Information Technology","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123177374","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 : 2008-12-01DOI: 10.1109/ISSPIT.2008.4775713
A. Ziaei, S. Ahadi, S. M. Mirrezaie, H. Yeganeh
In this paper, we present a new back-end classifier for GMM-LM based language identification systems. Our new proposed system consists of two main parts, mapping matrix and bank of SVMs. These two parts are located in series after GMM-LM system. The mapping matrix, maps the language models' output vectors to a new space in which the languages are more separable than before. Then each SVM in the SVM bank separates one language from the others. We used a new sequence kernel for each SVM in the bank. We show that our new sequence kernel-based SVMs separate languages more efficiently than common Gaussian mixture and GLDS SVM back-end classifiers. Also our new mapping matrix outperforms common linear discriminant matrix in separating classes from each other. Using these two parts increases the LID accuracy noticeably in comparison with the other LDA-GMM and LDA-GLDS SVM back-end classifiers. Our experiments on 5 languages from OGI-TS multilanguage task, prove our claim.
{"title":"Spoken Language Identification Using a New Sequence Kernel-based SVM Back-end Classifier","authors":"A. Ziaei, S. Ahadi, S. M. Mirrezaie, H. Yeganeh","doi":"10.1109/ISSPIT.2008.4775713","DOIUrl":"https://doi.org/10.1109/ISSPIT.2008.4775713","url":null,"abstract":"In this paper, we present a new back-end classifier for GMM-LM based language identification systems. Our new proposed system consists of two main parts, mapping matrix and bank of SVMs. These two parts are located in series after GMM-LM system. The mapping matrix, maps the language models' output vectors to a new space in which the languages are more separable than before. Then each SVM in the SVM bank separates one language from the others. We used a new sequence kernel for each SVM in the bank. We show that our new sequence kernel-based SVMs separate languages more efficiently than common Gaussian mixture and GLDS SVM back-end classifiers. Also our new mapping matrix outperforms common linear discriminant matrix in separating classes from each other. Using these two parts increases the LID accuracy noticeably in comparison with the other LDA-GMM and LDA-GLDS SVM back-end classifiers. Our experiments on 5 languages from OGI-TS multilanguage task, prove our claim.","PeriodicalId":213756,"journal":{"name":"2008 IEEE International Symposium on Signal Processing and Information Technology","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127790819","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 : 2008-12-01DOI: 10.1109/ISSPIT.2008.4775697
F. Foroozan, A. Asif
The paper derives time reversal (TR) algorithms for N-ary classification problems and studies the impact of multipaths on the performance characteristics of these algorithms. The TR classifiers have the ability of detecting the presence or absence of a target in a rich cluttering environment with multipaths and of further classifying the detected targets either as an unknown enemy target or one of the known friendly targets. Compared to the conventional classifiers, the proposed TR classifier provides a gain of over 5dB at low SNRs. An analytical multipath model, based on geometric optics approximation with strong total internal reflection from the boundaries of the medium, is used to compare the effect of multipaths on the proposed classifiers versus the conventional algorithms.
{"title":"Effect of Multipaths on N-Ary Time Reversal Classifiers","authors":"F. Foroozan, A. Asif","doi":"10.1109/ISSPIT.2008.4775697","DOIUrl":"https://doi.org/10.1109/ISSPIT.2008.4775697","url":null,"abstract":"The paper derives time reversal (TR) algorithms for N-ary classification problems and studies the impact of multipaths on the performance characteristics of these algorithms. The TR classifiers have the ability of detecting the presence or absence of a target in a rich cluttering environment with multipaths and of further classifying the detected targets either as an unknown enemy target or one of the known friendly targets. Compared to the conventional classifiers, the proposed TR classifier provides a gain of over 5dB at low SNRs. An analytical multipath model, based on geometric optics approximation with strong total internal reflection from the boundaries of the medium, is used to compare the effect of multipaths on the proposed classifiers versus the conventional algorithms.","PeriodicalId":213756,"journal":{"name":"2008 IEEE International Symposium on Signal Processing and Information Technology","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123692090","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 : 2008-12-01DOI: 10.1109/ISSPIT.2008.4775726
F. Derraz, A. Taleb-Ahmed, A. Chikh, F. Bereksi-Reguig, A. Pinti
Recently, a new reformulation of geometric active contour model is introduced by reformulating the gradient flow with Sobolev-type inner products. Classical inner product induces a pathological Riemannian metric on the space of smooth curves. However, there are also undesirable features associated with the gradient flow that this inner product induces. Sobolev metrics induce good regularity properties in gradient flow. The new formulation based Sobolev metric improved segmentation accuracy. We applied successfully the proposed model to synthetic and real MR images. The results drawn by the newer model are compared to expert segmentation and evaluated in term of F-measure.
{"title":"A Geometrical Active Contour Based Sobolev Metric","authors":"F. Derraz, A. Taleb-Ahmed, A. Chikh, F. Bereksi-Reguig, A. Pinti","doi":"10.1109/ISSPIT.2008.4775726","DOIUrl":"https://doi.org/10.1109/ISSPIT.2008.4775726","url":null,"abstract":"Recently, a new reformulation of geometric active contour model is introduced by reformulating the gradient flow with Sobolev-type inner products. Classical inner product induces a pathological Riemannian metric on the space of smooth curves. However, there are also undesirable features associated with the gradient flow that this inner product induces. Sobolev metrics induce good regularity properties in gradient flow. The new formulation based Sobolev metric improved segmentation accuracy. We applied successfully the proposed model to synthetic and real MR images. The results drawn by the newer model are compared to expert segmentation and evaluated in term of F-measure.","PeriodicalId":213756,"journal":{"name":"2008 IEEE International Symposium on Signal Processing and Information Technology","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126408598","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 : 2008-12-01DOI: 10.1109/ISSPIT.2008.4775648
I. Draganov, A. Popova, L.L. Ivanov
In this paper some aspects are presented for multilingual names database searching enhancement. They should help to find some balance between the execution time and the relevance of the results obtained. Structured form of the information used, two different structures of the database and a general algorithm for the searching are suggested. As experimental results investigation of the groupings of the most popular Romanized Bulgarian own names produced by the Soundex and Daitch-Mokotoff Soundex (D-M Soundex) algorithms are given. Then conclusion is made for their applicability.
{"title":"Multilingual Names Database Searching Enhancement","authors":"I. Draganov, A. Popova, L.L. Ivanov","doi":"10.1109/ISSPIT.2008.4775648","DOIUrl":"https://doi.org/10.1109/ISSPIT.2008.4775648","url":null,"abstract":"In this paper some aspects are presented for multilingual names database searching enhancement. They should help to find some balance between the execution time and the relevance of the results obtained. Structured form of the information used, two different structures of the database and a general algorithm for the searching are suggested. As experimental results investigation of the groupings of the most popular Romanized Bulgarian own names produced by the Soundex and Daitch-Mokotoff Soundex (D-M Soundex) algorithms are given. Then conclusion is made for their applicability.","PeriodicalId":213756,"journal":{"name":"2008 IEEE International Symposium on Signal Processing and Information Technology","volume":"373 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2008-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124665675","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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