Pub Date : 2010-07-07DOI: 10.1109/IPTA.2010.5586729
Ga-Young Kim, Byoung-Ik Kim, Tae-Wuk Bae, Young-Choon Kim, Sang-Ho Ahn, K. Sohng
In this paper, we implement a reticle seeker missile simulator on MATLAB-SIMULINK to analyze the jamming effect of the spin-scan and conscan reticle seeker. The DIRCM (Directed Infrared Countermeasures) system uses the pulsing flashes of infrared (IR) energy and its frequency and intensity have influence on the missile guidance system. Our simulation results show that jamming effect is indicated significantly when jammer frequency and reticle frequency are similar and present a 3D trajectory of missile motions by jamming.
{"title":"Implementation of a reticle seeker missile simulator for jamming effect analysis","authors":"Ga-Young Kim, Byoung-Ik Kim, Tae-Wuk Bae, Young-Choon Kim, Sang-Ho Ahn, K. Sohng","doi":"10.1109/IPTA.2010.5586729","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586729","url":null,"abstract":"In this paper, we implement a reticle seeker missile simulator on MATLAB-SIMULINK to analyze the jamming effect of the spin-scan and conscan reticle seeker. The DIRCM (Directed Infrared Countermeasures) system uses the pulsing flashes of infrared (IR) energy and its frequency and intensity have influence on the missile guidance system. Our simulation results show that jamming effect is indicated significantly when jammer frequency and reticle frequency are similar and present a 3D trajectory of missile motions by jamming.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126401895","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586805
ChingShun Lin, Daren Wang
In this paper we propose an image-based biological classification system that can identify different creatures via their sounds. The overall system involves the relative spectral transform-perceptual linear prediction for spectrogram image extraction, cosine similarity measure for feature matching, dynamic Hilbert curve for spectrogram routing, and Gaussian mixture model for 1-D spectrogram classification. As an example of our approach, results for honk, dolphin, and whale classification are presented. This method works well on a wide variety of bio-sounds, especially for the highly self-repeated ones. Applications of this approach include biological signal analysis and spectrogram library establishment.
{"title":"Spectrogram image encoding based on dynamic Hilbert curve routing","authors":"ChingShun Lin, Daren Wang","doi":"10.1109/IPTA.2010.5586805","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586805","url":null,"abstract":"In this paper we propose an image-based biological classification system that can identify different creatures via their sounds. The overall system involves the relative spectral transform-perceptual linear prediction for spectrogram image extraction, cosine similarity measure for feature matching, dynamic Hilbert curve for spectrogram routing, and Gaussian mixture model for 1-D spectrogram classification. As an example of our approach, results for honk, dolphin, and whale classification are presented. This method works well on a wide variety of bio-sounds, especially for the highly self-repeated ones. Applications of this approach include biological signal analysis and spectrogram library establishment.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132638545","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586747
Giap Nguyen, Mickaël Coustaty, J. Ogier
We commonly need to extract the image feature to understand and to realize the processes on it, and for each process we need a suitable feature extraction method. In this paper, we describe a stroke feature extraction method which will used in the lettrine indexing. A lettrine is a letter decorated who appear at the beginning of a chapter or a paragraph in ancient books. It's principally composed of strokes. This method is developed with the goal to characterize for indexing them by content using these particular components. We thus use strokes instead of pixels as elementary component. This study is innovative and first results are interesting. Indexing tests using this method will be made in the NaviDoMass project1.
{"title":"Stroke feature extraction for lettrine indexing","authors":"Giap Nguyen, Mickaël Coustaty, J. Ogier","doi":"10.1109/IPTA.2010.5586747","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586747","url":null,"abstract":"We commonly need to extract the image feature to understand and to realize the processes on it, and for each process we need a suitable feature extraction method. In this paper, we describe a stroke feature extraction method which will used in the lettrine indexing. A lettrine is a letter decorated who appear at the beginning of a chapter or a paragraph in ancient books. It's principally composed of strokes. This method is developed with the goal to characterize for indexing them by content using these particular components. We thus use strokes instead of pixels as elementary component. This study is innovative and first results are interesting. Indexing tests using this method will be made in the NaviDoMass project1.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131857018","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586762
Mauritz Panggabean, Stig Salater, L. A. Rønningen
This paper investigates the use of eye tracking to define the important objects in a scene, i.e. those focused by viewers. These objects are rich in information, such as human face. They should be coded with higher quality than unfocused ones as in foveated video coding, for which eye tracking can serve as a preliminary step. We show that human gaze points often cover only a very small area of the screen, even less than 10%, providing great opportunities to save much more bit rate. Gaze points from a number of subjects watching a scene can be represented compactly in the proposed box diagram, another contribution from this work, that can give simple description of the scene just in a one diagram.
{"title":"Eye tracking for foveation video coding and simple scene description","authors":"Mauritz Panggabean, Stig Salater, L. A. Rønningen","doi":"10.1109/IPTA.2010.5586762","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586762","url":null,"abstract":"This paper investigates the use of eye tracking to define the important objects in a scene, i.e. those focused by viewers. These objects are rich in information, such as human face. They should be coded with higher quality than unfocused ones as in foveated video coding, for which eye tracking can serve as a preliminary step. We show that human gaze points often cover only a very small area of the screen, even less than 10%, providing great opportunities to save much more bit rate. Gaze points from a number of subjects watching a scene can be represented compactly in the proposed box diagram, another contribution from this work, that can give simple description of the scene just in a one diagram.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129231289","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586739
A. Karami, M. Yazdi, A. Z. Asli
In this paper, an efficient method for Hyperspectral image compression based on the Tucker Decomposition (TD) and the Three Dimensional Discrete Cosine Transform (3D-DCT) is proposed. The core idea behind our proposed technique is to apply TD to the 3D-DCT coefficients of Hyperspectral image in order to not only exploit redundancies between bands but also to use spatial correlations of every image band and therefore, as simulation results applied to real Hyperspectral images demonstrate, it leads to a remarkable compression ratio with improved quality.
{"title":"Hyperspectral image compression based on Tucker Decomposition and Discrete Cosine Transform","authors":"A. Karami, M. Yazdi, A. Z. Asli","doi":"10.1109/IPTA.2010.5586739","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586739","url":null,"abstract":"In this paper, an efficient method for Hyperspectral image compression based on the Tucker Decomposition (TD) and the Three Dimensional Discrete Cosine Transform (3D-DCT) is proposed. The core idea behind our proposed technique is to apply TD to the 3D-DCT coefficients of Hyperspectral image in order to not only exploit redundancies between bands but also to use spatial correlations of every image band and therefore, as simulation results applied to real Hyperspectral images demonstrate, it leads to a remarkable compression ratio with improved quality.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129293054","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586733
H. Al-Muscati, F. Labeau
In this work, a novel implementation of a video transcoder that converts a video sequence encoded with the H.264/AVC standard to a temporally scalable H.264/SVC stream is achieved with the use of a pixel-domain heterogeneous architecture. The input H.264/AVC stream is fully decoded by the transcoder. Macroblock coding modes are extracted from the input stream and are reused to encode the output stream. A set of new motion vectors is computed from the input stream coded motion vectors, and are mapped to either the hierarchical B-frame or zero-delay referencing structures employed by H.264/SVC. These new motion vectors are further subjected to a 3 pixel refinement. As a result, a significant decrease in computational complexity is achieved, while maintaining a close to optimum compression efficiency.
{"title":"Temporal transcoding of H.264/AVC video to the scalable format","authors":"H. Al-Muscati, F. Labeau","doi":"10.1109/IPTA.2010.5586733","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586733","url":null,"abstract":"In this work, a novel implementation of a video transcoder that converts a video sequence encoded with the H.264/AVC standard to a temporally scalable H.264/SVC stream is achieved with the use of a pixel-domain heterogeneous architecture. The input H.264/AVC stream is fully decoded by the transcoder. Macroblock coding modes are extracted from the input stream and are reused to encode the output stream. A set of new motion vectors is computed from the input stream coded motion vectors, and are mapped to either the hierarchical B-frame or zero-delay referencing structures employed by H.264/SVC. These new motion vectors are further subjected to a 3 pixel refinement. As a result, a significant decrease in computational complexity is achieved, while maintaining a close to optimum compression efficiency.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"108 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133177486","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586731
Saurav Kumar, A. Rai, Akhilesh Agarwal, Nisha Bachani
This research work is related to the application of machine vision technique to develop a robust assistive human computer interaction technology for those with physical accessibility problem of controlling mouse and keyboard with hand. Paper's main motif is inferring information about planer movement of the head using a video camera and transforming this motion to the pixel coordinate system of the display so as to control the position of mouse pointer. Iterative sparse optical flow algorithm computes the pattern of apparent motion between sequential facial image frames captured by the webcam. Adaboost based Cascaded Harr classifier is used to detect face and eye across frames and we have given special attention towards the issues involving drawback regarding misdetection of tilted faces in the image frame inspite of training our datasets with tilted facial images. Left/Right eye blink is used to control the clicking event of mouse. Blink of eye is modelled by fitting the trained data using Spline and Gaussian curve which determines the likelihood function to determine the posterior probability. This work is motivated by the need to design an affordable real-time system in the interest of a large serving community.
{"title":"Vision based human interaction system for disabled","authors":"Saurav Kumar, A. Rai, Akhilesh Agarwal, Nisha Bachani","doi":"10.1109/IPTA.2010.5586731","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586731","url":null,"abstract":"This research work is related to the application of machine vision technique to develop a robust assistive human computer interaction technology for those with physical accessibility problem of controlling mouse and keyboard with hand. Paper's main motif is inferring information about planer movement of the head using a video camera and transforming this motion to the pixel coordinate system of the display so as to control the position of mouse pointer. Iterative sparse optical flow algorithm computes the pattern of apparent motion between sequential facial image frames captured by the webcam. Adaboost based Cascaded Harr classifier is used to detect face and eye across frames and we have given special attention towards the issues involving drawback regarding misdetection of tilted faces in the image frame inspite of training our datasets with tilted facial images. Left/Right eye blink is used to control the clicking event of mouse. Blink of eye is modelled by fitting the trained data using Spline and Gaussian curve which determines the likelihood function to determine the posterior probability. This work is motivated by the need to design an affordable real-time system in the interest of a large serving community.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123282543","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586732
Xueyi Zhao
This paper proposes a novel technique for learning face features based on Bayesian regularized non-negative matrix factorization with Itakura-Saito (IS) divergence (B-NMF). In this paper, we show, the proposed technique not only explicitly incorporates the notion of ‘Bayesian regularized prior’ which imposes onto the features learning but also holds the property of scale invariant that enables lower energy components in the learning process to be treated with equal importance as the high energy components. Real test has been conducted and the obtained results are very encouraging.
{"title":"Bayesian regularized nonnegative matrix factorization based face features learning","authors":"Xueyi Zhao","doi":"10.1109/IPTA.2010.5586732","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586732","url":null,"abstract":"This paper proposes a novel technique for learning face features based on Bayesian regularized non-negative matrix factorization with Itakura-Saito (IS) divergence (B-NMF). In this paper, we show, the proposed technique not only explicitly incorporates the notion of ‘Bayesian regularized prior’ which imposes onto the features learning but also holds the property of scale invariant that enables lower energy components in the learning process to be treated with equal importance as the high energy components. Real test has been conducted and the obtained results are very encouraging.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114213236","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586760
A. Porebski, N. Vandenbroucke, L. Macaire
In this paper, we propose to compare the performances of two sequential feature selection schemes used for supervised color texture classification. We focus this study on the sequential forward selection (SFS) scheme and the more complex sequential forward floating selection (SFFS) scheme which avoids the “nesting effect”. These schemes retain Haralick features extracted from chromatic co-occurrence matrices of images coded in different color spaces. We experimentally study the contribution of these two feature selection schemes with three benchmark color texture databases.
{"title":"Comparison of feature selection schemes for color texture classification","authors":"A. Porebski, N. Vandenbroucke, L. Macaire","doi":"10.1109/IPTA.2010.5586760","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586760","url":null,"abstract":"In this paper, we propose to compare the performances of two sequential feature selection schemes used for supervised color texture classification. We focus this study on the sequential forward selection (SFS) scheme and the more complex sequential forward floating selection (SFFS) scheme which avoids the “nesting effect”. These schemes retain Haralick features extracted from chromatic co-occurrence matrices of images coded in different color spaces. We experimentally study the contribution of these two feature selection schemes with three benchmark color texture databases.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121686419","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 : 2010-07-07DOI: 10.1109/IPTA.2010.5586748
Pierre Boudoin, H. Maaref, S. Otmane, M. Mallem
This paper aims to present all the study done on the SPIDAR, which is a tracking and haptic device, in order to improve its accuracy on the given position. Firstly we proposed a new semi-automatic initialization technique for this device using an optical tracking system. Then, we propose to use Support Vector Regression (SVR) to calibrate the SPIDAR in order to reduce location errors. We obtained very good results with this calibration, since we reduced the mean error by more than 50%.
{"title":"SPIDAR calibration using Support Vector Regression","authors":"Pierre Boudoin, H. Maaref, S. Otmane, M. Mallem","doi":"10.1109/IPTA.2010.5586748","DOIUrl":"https://doi.org/10.1109/IPTA.2010.5586748","url":null,"abstract":"This paper aims to present all the study done on the SPIDAR, which is a tracking and haptic device, in order to improve its accuracy on the given position. Firstly we proposed a new semi-automatic initialization technique for this device using an optical tracking system. Then, we propose to use Support Vector Regression (SVR) to calibrate the SPIDAR in order to reduce location errors. We obtained very good results with this calibration, since we reduced the mean error by more than 50%.","PeriodicalId":236574,"journal":{"name":"2010 2nd International Conference on Image Processing Theory, Tools and Applications","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125142122","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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