Pub Date : 2010-07-05DOI: 10.1109/ICSPS.2010.5555460
Kou Ziming, Wei Xiuye, Wu Juan, Zhang Huixian
The hydraulic vibration system excited by wave exciter is established. After analysis on Poisson coupling and Junction coupling in excited vibration system 4-eqation dynamics model on liquid flowing, pressure fluctuation and pipe vibration is adopted, and numerical analysis of fluid–solid coupled vibration system excited by wave exciter is carried out by using method of characteristics. The results of numerical analysis show that pressure wave velocity is descending, and vibration periodicity prolongs because of Poisson coupling; at the same time, stress wave velocity of pipe is increasing, and vibration periodicity is shortened. The results of numerical analysis agree with those of experiment.
{"title":"Analysis of fluid-structure interaction vibration response for vibration system excited by wave exciter","authors":"Kou Ziming, Wei Xiuye, Wu Juan, Zhang Huixian","doi":"10.1109/ICSPS.2010.5555460","DOIUrl":"https://doi.org/10.1109/ICSPS.2010.5555460","url":null,"abstract":"The hydraulic vibration system excited by wave exciter is established. After analysis on Poisson coupling and Junction coupling in excited vibration system 4-eqation dynamics model on liquid flowing, pressure fluctuation and pipe vibration is adopted, and numerical analysis of fluid–solid coupled vibration system excited by wave exciter is carried out by using method of characteristics. The results of numerical analysis show that pressure wave velocity is descending, and vibration periodicity prolongs because of Poisson coupling; at the same time, stress wave velocity of pipe is increasing, and vibration periodicity is shortened. The results of numerical analysis agree with those of experiment.","PeriodicalId":234084,"journal":{"name":"2010 2nd International Conference on Signal Processing Systems","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130167272","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 : 2010-07-05DOI: 10.1109/ICSPS.2010.5555773
Lin Junhuan, Chen Yuefen
Information hiding technology is studied in this paper, and a new image hiding algorithm based on intensity quantization and block random scrambling is proposed in this paper. The information is embedded into the carrier image in space domain, and when reconstructing the secret information, noise detection is performed before inverse quantization. A simple system of image hiding and extraction using the proposed algorithm based on Matlab is realized, and its resistance to noising, cropping and scribbling is simulated Results verifies the validity of the proposed algorithm and it has the advantages of simple implementation, large hiding capacity and good anti-noising and cropping performance.
{"title":"Image hiding and extraction algorithm based on intensity quantization and block random scrambling","authors":"Lin Junhuan, Chen Yuefen","doi":"10.1109/ICSPS.2010.5555773","DOIUrl":"https://doi.org/10.1109/ICSPS.2010.5555773","url":null,"abstract":"Information hiding technology is studied in this paper, and a new image hiding algorithm based on intensity quantization and block random scrambling is proposed in this paper. The information is embedded into the carrier image in space domain, and when reconstructing the secret information, noise detection is performed before inverse quantization. A simple system of image hiding and extraction using the proposed algorithm based on Matlab is realized, and its resistance to noising, cropping and scribbling is simulated Results verifies the validity of the proposed algorithm and it has the advantages of simple implementation, large hiding capacity and good anti-noising and cropping performance.","PeriodicalId":234084,"journal":{"name":"2010 2nd International Conference on Signal Processing Systems","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130171305","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 : 2010-07-05DOI: 10.1109/ICSPS.2010.5555858
Hairong Jia, Xueying Zhang, Chensheng Jin
A speech enhancement method based on wavelet packet transform and hearing masking effect is proposed. This method has following steps. Firstly, by perceptual wavelet packet the noisy speech is enhanced. Then by Johnston hearing masking model the noise hearing masking threshold is gained. Finally, by a perceptual filter based on hearing masking effect the enhanced speech is smoothed, the clean speech is gained. Simulation results show that under the background of white, the SNR and PESQ (Perceptual Evaluation of Speech Quality) in this method are more excellent than in the traditional wavelet packet method, meanwhile the musical noise after the enhancement is depressed effectively.
{"title":"A speech enhancement method based on wavelet packet and hearing masking effect","authors":"Hairong Jia, Xueying Zhang, Chensheng Jin","doi":"10.1109/ICSPS.2010.5555858","DOIUrl":"https://doi.org/10.1109/ICSPS.2010.5555858","url":null,"abstract":"A speech enhancement method based on wavelet packet transform and hearing masking effect is proposed. This method has following steps. Firstly, by perceptual wavelet packet the noisy speech is enhanced. Then by Johnston hearing masking model the noise hearing masking threshold is gained. Finally, by a perceptual filter based on hearing masking effect the enhanced speech is smoothed, the clean speech is gained. Simulation results show that under the background of white, the SNR and PESQ (Perceptual Evaluation of Speech Quality) in this method are more excellent than in the traditional wavelet packet method, meanwhile the musical noise after the enhancement is depressed effectively.","PeriodicalId":234084,"journal":{"name":"2010 2nd International Conference on Signal Processing Systems","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122364130","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 : 2010-07-05DOI: 10.1109/ICSPS.2010.5555637
Michal Prauzek, T. Peterek, O. Adamec, M. Penhaker
This paper describes signal preprocessing of photoplethysmograph record on hardware platform. The constructed device includes basic signal measurement, low-pass and high-pass filtration. The filters are realized by second order Butterworth filters and they are describes by transfer functions. All measurement contains frequency analysis for verification of frequency distortion.
{"title":"Analog signal preprocessing in reflected Plethysmography","authors":"Michal Prauzek, T. Peterek, O. Adamec, M. Penhaker","doi":"10.1109/ICSPS.2010.5555637","DOIUrl":"https://doi.org/10.1109/ICSPS.2010.5555637","url":null,"abstract":"This paper describes signal preprocessing of photoplethysmograph record on hardware platform. The constructed device includes basic signal measurement, low-pass and high-pass filtration. The filters are realized by second order Butterworth filters and they are describes by transfer functions. All measurement contains frequency analysis for verification of frequency distortion.","PeriodicalId":234084,"journal":{"name":"2010 2nd International Conference on Signal Processing Systems","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123735846","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 : 2010-07-05DOI: 10.1109/ICSPS.2010.5555499
Musheng Chen
Different angle shot image from CCD will affect the accuracy of image measurement. To improve the measurement accuracy, a new geometry correction method for angle shot image is presented. Establishing geometry relations between the image plane and the object plane, which is based on the theory of camera imaging, we can obtain the adjusted geometry parameter which can adjust measurement error, increase digital image measuring accuracy, reduce the shooting angle limit and expand the application scope of image measurement in a certain degree. Experiment indicate that this method shows perfect results, the range of uncertainty is less than two image elements.
{"title":"Geometry correction method of sloped shoot image","authors":"Musheng Chen","doi":"10.1109/ICSPS.2010.5555499","DOIUrl":"https://doi.org/10.1109/ICSPS.2010.5555499","url":null,"abstract":"Different angle shot image from CCD will affect the accuracy of image measurement. To improve the measurement accuracy, a new geometry correction method for angle shot image is presented. Establishing geometry relations between the image plane and the object plane, which is based on the theory of camera imaging, we can obtain the adjusted geometry parameter which can adjust measurement error, increase digital image measuring accuracy, reduce the shooting angle limit and expand the application scope of image measurement in a certain degree. Experiment indicate that this method shows perfect results, the range of uncertainty is less than two image elements.","PeriodicalId":234084,"journal":{"name":"2010 2nd International Conference on Signal Processing Systems","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130706780","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 : 2010-07-05DOI: 10.1109/ICSPS.2010.5555580
R. Akbari, Mehdi Keshavarz Bahaghighat, J. Mohammadi
One of the main challenges faced by the current face recognition techniques lies in the difficulties of collecting samples. Fewer samples per person mean less laborious effort for collecting them, lower cost for storing and processing them. Unfortunately, many reported face recognition techniques rely heavily on the size and representative of training set, and most of them will suffer serious performance drop or even fail to work if only one training sample per person is available to the systems. In this paper, a recognition algorithm based on feature vectors of Legendre moments is introduced as an attempt to solve the single image problem. Subset of 200 images from FERET database and 100 images from AR database are used in our experiments. The results reported in this paper show that the proposed method achieves 91% and 89.5% accuracy for AR and FERET, respectively.
{"title":"Legendre moments for face identification based on single image per person","authors":"R. Akbari, Mehdi Keshavarz Bahaghighat, J. Mohammadi","doi":"10.1109/ICSPS.2010.5555580","DOIUrl":"https://doi.org/10.1109/ICSPS.2010.5555580","url":null,"abstract":"One of the main challenges faced by the current face recognition techniques lies in the difficulties of collecting samples. Fewer samples per person mean less laborious effort for collecting them, lower cost for storing and processing them. Unfortunately, many reported face recognition techniques rely heavily on the size and representative of training set, and most of them will suffer serious performance drop or even fail to work if only one training sample per person is available to the systems. In this paper, a recognition algorithm based on feature vectors of Legendre moments is introduced as an attempt to solve the single image problem. Subset of 200 images from FERET database and 100 images from AR database are used in our experiments. The results reported in this paper show that the proposed method achieves 91% and 89.5% accuracy for AR and FERET, respectively.","PeriodicalId":234084,"journal":{"name":"2010 2nd International Conference on Signal Processing Systems","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130723938","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 : 2010-07-05DOI: 10.1109/ICSPS.2010.5555797
Wang Jiegui, Yin Xuezhong
A novel method of maneuvering target location by single station with radio signal is proposed in this paper. Firstly, based on the measurement of Time Difference of Arrival (TDOA) and the Direction of Arrival (DOA) of the non-cooperative FM radio illuminators, the maneuvering model and the measurement equation are built. Secondly, the Maximum-Likelihood Estimate Interacting Multiple-Model (MLE-IMM) algorithm for location of maneuvering target is proposed. With the help of computer simulation, the proposed method is proven to be practicable and effective.
{"title":"MLE-IMM algorithm of maneuvering target location by single station with radio signal","authors":"Wang Jiegui, Yin Xuezhong","doi":"10.1109/ICSPS.2010.5555797","DOIUrl":"https://doi.org/10.1109/ICSPS.2010.5555797","url":null,"abstract":"A novel method of maneuvering target location by single station with radio signal is proposed in this paper. Firstly, based on the measurement of Time Difference of Arrival (TDOA) and the Direction of Arrival (DOA) of the non-cooperative FM radio illuminators, the maneuvering model and the measurement equation are built. Secondly, the Maximum-Likelihood Estimate Interacting Multiple-Model (MLE-IMM) algorithm for location of maneuvering target is proposed. With the help of computer simulation, the proposed method is proven to be practicable and effective.","PeriodicalId":234084,"journal":{"name":"2010 2nd International Conference on Signal Processing Systems","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132423820","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 : 2010-07-05DOI: 10.1109/ICSPS.2010.5555494
Jiang Hao, Xu Jie
This paper proposes an effective method to scene recognition based on bags-of-words (BoW) algorithm. Current scene classification methods usually treat all the codewords equally important when using BoW histogram to represent an image. This assumption, however, does not comply with many real-world conditions as different codewords usually have different discriminating power when representing different scene categories. Considering this, this paper proposes an effective technique to perform scene recognition. It first uses k-means algorithm to construct a codebook, in addition with an occurrence matrix. The importance of each codeword for each scene category is then estimated based on the above cooccurrence matrix. Finally this discrimination information is incorporated into the original BoW histogram of the image and produces a new BoW histogram. Support vector machine (SVM) is used to train these BoW histograms. Experimental results on the 15 scene dataset show that the proposed method is very effective compared with state-of-art works.
{"title":"Improved bags-of-words algorithm for scene recognition","authors":"Jiang Hao, Xu Jie","doi":"10.1109/ICSPS.2010.5555494","DOIUrl":"https://doi.org/10.1109/ICSPS.2010.5555494","url":null,"abstract":"This paper proposes an effective method to scene recognition based on bags-of-words (BoW) algorithm. Current scene classification methods usually treat all the codewords equally important when using BoW histogram to represent an image. This assumption, however, does not comply with many real-world conditions as different codewords usually have different discriminating power when representing different scene categories. Considering this, this paper proposes an effective technique to perform scene recognition. It first uses k-means algorithm to construct a codebook, in addition with an occurrence matrix. The importance of each codeword for each scene category is then estimated based on the above cooccurrence matrix. Finally this discrimination information is incorporated into the original BoW histogram of the image and produces a new BoW histogram. Support vector machine (SVM) is used to train these BoW histograms. Experimental results on the 15 scene dataset show that the proposed method is very effective compared with state-of-art works.","PeriodicalId":234084,"journal":{"name":"2010 2nd International Conference on Signal Processing Systems","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131972090","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 : 2010-07-05DOI: 10.1109/ICSPS.2010.5555441
Ning Liu, Xiaowei Kong, W. Xia, Zishu He
This paper presents a design of close-loop digital predistorter (DPD) for Power Amplifier (PA), which can be fully performed in a Field Programmable Gate Array(FPGA) without the need of additional Digital Signal Processor(DSP) or Personal Computer(PC) to run the procedure of adaptation. The adaptation of look-up table of the Nonlinear Auto Regressive Moving Average (NARMA) model is realized by Least Mean Square (LMS) algorithm and the mapping relationship in the structure. Specific details of the LMS algorithm and the mapping relationship are provided. Finally, the results of an FPGA implementation demonstrate the performance (adjacent channel power ratio and error vector magnitude) of PA can be improved by our method.
{"title":"An LMS-based close-loop digital predistorter for RF power amplifiers using NARMA structure","authors":"Ning Liu, Xiaowei Kong, W. Xia, Zishu He","doi":"10.1109/ICSPS.2010.5555441","DOIUrl":"https://doi.org/10.1109/ICSPS.2010.5555441","url":null,"abstract":"This paper presents a design of close-loop digital predistorter (DPD) for Power Amplifier (PA), which can be fully performed in a Field Programmable Gate Array(FPGA) without the need of additional Digital Signal Processor(DSP) or Personal Computer(PC) to run the procedure of adaptation. The adaptation of look-up table of the Nonlinear Auto Regressive Moving Average (NARMA) model is realized by Least Mean Square (LMS) algorithm and the mapping relationship in the structure. Specific details of the LMS algorithm and the mapping relationship are provided. Finally, the results of an FPGA implementation demonstrate the performance (adjacent channel power ratio and error vector magnitude) of PA can be improved by our method.","PeriodicalId":234084,"journal":{"name":"2010 2nd International Conference on Signal Processing Systems","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132059084","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 : 2010-07-05DOI: 10.1109/ICSPS.2010.5555260
A. Nasrabadi, J. Haddadnia
Face detection is a famous work that recently considered for surveillence system especialy in complex background is a challenging task. The complexity in such detection systems stems from the variances in image background, view, illumination, articulation, and facial expression. This article is allocated to introducing a new algorithm for face detection. Skin color detection base on fuzzy gaussian filter accuracy adjustment and template matching composed our method instrument. At this paper non-skin parts in the pictures omitted firstly and then result passed to template matching section. Fuzzy adjustment implemented by noise ratio that earned at this paper from noise profile that segmented by Wavelet transform. Easy implementation and high accuracy detection be feature of our work in compare with other works and indicate the superiority of our work.
{"title":"Face detection base on wavelet and fuzzy adjustment","authors":"A. Nasrabadi, J. Haddadnia","doi":"10.1109/ICSPS.2010.5555260","DOIUrl":"https://doi.org/10.1109/ICSPS.2010.5555260","url":null,"abstract":"Face detection is a famous work that recently considered for surveillence system especialy in complex background is a challenging task. The complexity in such detection systems stems from the variances in image background, view, illumination, articulation, and facial expression. This article is allocated to introducing a new algorithm for face detection. Skin color detection base on fuzzy gaussian filter accuracy adjustment and template matching composed our method instrument. At this paper non-skin parts in the pictures omitted firstly and then result passed to template matching section. Fuzzy adjustment implemented by noise ratio that earned at this paper from noise profile that segmented by Wavelet transform. Easy implementation and high accuracy detection be feature of our work in compare with other works and indicate the superiority of our work.","PeriodicalId":234084,"journal":{"name":"2010 2nd International Conference on Signal Processing Systems","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2010-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132069357","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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