Pub Date : 2012-10-01DOI: 10.4156/JNIT.VOL4.ISSUE1.3
Zhang Qi-gui, Zhao Lijuan
This paper is mainly about an image reconstruction algorithm, which based on bayer template. First, to estimate other components' gradient information through the information of G, according to each component's gradient correlation, including R, G and B. And then get other component's values. The bayer image, whose resolution ratio is 1280*1024, 25 frames per second, captured by CMOS, is output by DVI interface or stored in memory after being interpolated and raised frame. The algorithm is verified on FPGA platform. The experiment shows that the reconstruction image's quality is very high and the PSNR is high to 37 dB.
{"title":"Implementation of bayer image interpolation based on FPGA","authors":"Zhang Qi-gui, Zhao Lijuan","doi":"10.4156/JNIT.VOL4.ISSUE1.3","DOIUrl":"https://doi.org/10.4156/JNIT.VOL4.ISSUE1.3","url":null,"abstract":"This paper is mainly about an image reconstruction algorithm, which based on bayer template. First, to estimate other components' gradient information through the information of G, according to each component's gradient correlation, including R, G and B. And then get other component's values. The bayer image, whose resolution ratio is 1280*1024, 25 frames per second, captured by CMOS, is output by DVI interface or stored in memory after being interpolated and raised frame. The algorithm is verified on FPGA platform. The experiment shows that the reconstruction image's quality is very high and the PSNR is high to 37 dB.","PeriodicalId":105832,"journal":{"name":"2012 6th International Conference on New Trends in Information Science, Service Science and Data Mining (ISSDM2012)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124261850","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 : 2012-10-01DOI: 10.4156/IJIPM.VOL4.ISSUE2.1
N. Thammakoranonta, C. Chayawan, K. Mongkonchoo
This manuscript investigates the abuse of Internet usage by college students in Bangkok and metropolitan areas. The remarkable results show that sensation seeking is the important factor to create the abuse of Internet and abuse behavior in computer. Some suggestions are also provided to reduce the problem.
{"title":"The abuse of Internet usage by undergraduates in Bangkok and vicinity","authors":"N. Thammakoranonta, C. Chayawan, K. Mongkonchoo","doi":"10.4156/IJIPM.VOL4.ISSUE2.1","DOIUrl":"https://doi.org/10.4156/IJIPM.VOL4.ISSUE2.1","url":null,"abstract":"This manuscript investigates the abuse of Internet usage by college students in Bangkok and metropolitan areas. The remarkable results show that sensation seeking is the important factor to create the abuse of Internet and abuse behavior in computer. Some suggestions are also provided to reduce the problem.","PeriodicalId":105832,"journal":{"name":"2012 6th International Conference on New Trends in Information Science, Service Science and Data Mining (ISSDM2012)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126621399","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 : 2012-10-01DOI: 10.4156/IJIPM.VOL4.ISSUE1.12
T. Kamimura, A. Kanasugi
Genetic algorithm (GA) is one of optimization algorithm based on an idea for evolution of life. GA can be applied various combination optimization problem. This paper proposes a parallel processor for distributed genetic algorithm (DGA) with redundant binary number. Since a redundant binary number has redundancy, solution expression becomes variegated. For this reason, it is expected the algorithm easily find the optimized solution, and the error rates decrease. Since DGA is a parallel algorithm, the performance can be improved by using a specified parallel processor. The effectiveness of the proposed processor was confirmed by some simulations and experiments using FPGA circuit board.
{"title":"A parallel processor for distributed genetic algorithm with redundant binary number","authors":"T. Kamimura, A. Kanasugi","doi":"10.4156/IJIPM.VOL4.ISSUE1.12","DOIUrl":"https://doi.org/10.4156/IJIPM.VOL4.ISSUE1.12","url":null,"abstract":"Genetic algorithm (GA) is one of optimization algorithm based on an idea for evolution of life. GA can be applied various combination optimization problem. This paper proposes a parallel processor for distributed genetic algorithm (DGA) with redundant binary number. Since a redundant binary number has redundancy, solution expression becomes variegated. For this reason, it is expected the algorithm easily find the optimized solution, and the error rates decrease. Since DGA is a parallel algorithm, the performance can be improved by using a specified parallel processor. The effectiveness of the proposed processor was confirmed by some simulations and experiments using FPGA circuit board.","PeriodicalId":105832,"journal":{"name":"2012 6th International Conference on New Trends in Information Science, Service Science and Data Mining (ISSDM2012)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128204387","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 : 2012-10-01DOI: 10.4156/IJIIP.VOL4.ISSUE1.1
G. He, Jinye Peng, Xiaoyi Feng, Jun Wang
Aiming at classifying multisource remote sensing images, we first introduce a Markov Random Field (MRF) to build prior probability models for multiple object classes. The Expectation Maximization-Hierarchical Markov Random Field (EM-HMRF) algorithm is then introduced to take advantage of the equivalence relation between the EM-HMRF and the fuzzy classification method. Second, this paper focused on exploiting self-adaptivity for selecting the prior distribution model parameter β automatically, and then two fusion schemes (centralized-based and distributed-based fusion) are introduced to achieve better classification results. A new algorithm is derived for supporting multisource remote sensing image classification by using image fusion and the EM-HMRF. The experimental results on synthetic images and real remote sensing images indicate that our proposed algorithm with two fusion schemes can not only greatly improve the accuracy of image classification but also strengthen the anti-interference of noise, thereby providing good evidence to support the effectiveness and superiority of our proposed algorithm in solving multisource remote sensing image classification problems. Our proposed algorithm for image classification with a fusion scheme should have great potential value for multisource remote sensing image classification strategies.
{"title":"Research on multisource remote sensing image classification algorithms based on image fusion and the EM-HMRF","authors":"G. He, Jinye Peng, Xiaoyi Feng, Jun Wang","doi":"10.4156/IJIIP.VOL4.ISSUE1.1","DOIUrl":"https://doi.org/10.4156/IJIIP.VOL4.ISSUE1.1","url":null,"abstract":"Aiming at classifying multisource remote sensing images, we first introduce a Markov Random Field (MRF) to build prior probability models for multiple object classes. The Expectation Maximization-Hierarchical Markov Random Field (EM-HMRF) algorithm is then introduced to take advantage of the equivalence relation between the EM-HMRF and the fuzzy classification method. Second, this paper focused on exploiting self-adaptivity for selecting the prior distribution model parameter β automatically, and then two fusion schemes (centralized-based and distributed-based fusion) are introduced to achieve better classification results. A new algorithm is derived for supporting multisource remote sensing image classification by using image fusion and the EM-HMRF. The experimental results on synthetic images and real remote sensing images indicate that our proposed algorithm with two fusion schemes can not only greatly improve the accuracy of image classification but also strengthen the anti-interference of noise, thereby providing good evidence to support the effectiveness and superiority of our proposed algorithm in solving multisource remote sensing image classification problems. Our proposed algorithm for image classification with a fusion scheme should have great potential value for multisource remote sensing image classification strategies.","PeriodicalId":105832,"journal":{"name":"2012 6th International Conference on New Trends in Information Science, Service Science and Data Mining (ISSDM2012)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128348002","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 : 2012-10-01DOI: 10.4156/IJIPM.VOL4.ISSUE4.7
Liu Wei, Zhu Hui
As a kind of new electronic commerce mode, groupon has changed the way people was used to consume because of lower cost, more competitive price, higher efficiency. This paper aims to delineate a theory of technology acceptance model, using Gefen (2003) as its basic theory, and combining the truth of online groupon with the professional ability of information senders. At the same time, we add some concepts such as brands of business and groupon websites, consumers' trust and the ability of community message senders. We got the data through college students by the 208 questionnaires. The empirical result indicates that business brand and groupon web sites quality are having the positive correlation with the trust of customers. This conclusion will provide decisive support to improve consumers' willingness to join online groupon.
{"title":"Empirical research on the groupon technology acceptance mode","authors":"Liu Wei, Zhu Hui","doi":"10.4156/IJIPM.VOL4.ISSUE4.7","DOIUrl":"https://doi.org/10.4156/IJIPM.VOL4.ISSUE4.7","url":null,"abstract":"As a kind of new electronic commerce mode, groupon has changed the way people was used to consume because of lower cost, more competitive price, higher efficiency. This paper aims to delineate a theory of technology acceptance model, using Gefen (2003) as its basic theory, and combining the truth of online groupon with the professional ability of information senders. At the same time, we add some concepts such as brands of business and groupon websites, consumers' trust and the ability of community message senders. We got the data through college students by the 208 questionnaires. The empirical result indicates that business brand and groupon web sites quality are having the positive correlation with the trust of customers. This conclusion will provide decisive support to improve consumers' willingness to join online groupon.","PeriodicalId":105832,"journal":{"name":"2012 6th International Conference on New Trends in Information Science, Service Science and Data Mining (ISSDM2012)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2012-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123144962","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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