Pub Date : 2017-01-31DOI: 10.15866/IRECOS.V12I1.11735
O. V. Putra, Budi Prianto, A. Prayitno, Esther Irawati Setiawan, E. M. Yuniarno, M. Purnomo
A crater lake of Mt. Kelud active volcano formed after the eruption on February, 2014. Real time surveillance has been conducted for 24 hours using a CCTV camera on the top of the summit. The primary purpose of this observation is monitoring the volcanic activity, such as degassing and discoloration of crater lake water. These phenomenons became the symptoms of the volcanic activity. The weather condition is continuously changes between clear, cloudy, and hazy. Obviously, camera vision is obscured or even blocked by haze. Another problem is that airlight source is hard to estimate because the lake color tends to be brighter in clear conditions. In this paper, a dehazing technique is proposed based on color attenuation prior and contrast enhancement. In contrast enhancement, the transmission map was enhanced using adaptive gamma correction. Our data were analyzed using referenceless fog density estimation (FADE). Our experimental results give the best result when it comes to fog density (by 1.60912 density) compared to previous algorithms.
{"title":"A Novel Approach on Dehazing Volcanic Crater Lake Hazy Scene Videos Based on Color Attenuation Prior","authors":"O. V. Putra, Budi Prianto, A. Prayitno, Esther Irawati Setiawan, E. M. Yuniarno, M. Purnomo","doi":"10.15866/IRECOS.V12I1.11735","DOIUrl":"https://doi.org/10.15866/IRECOS.V12I1.11735","url":null,"abstract":"A crater lake of Mt. Kelud active volcano formed after the eruption on February, 2014. Real time surveillance has been conducted for 24 hours using a CCTV camera on the top of the summit. The primary purpose of this observation is monitoring the volcanic activity, such as degassing and discoloration of crater lake water. These phenomenons became the symptoms of the volcanic activity. The weather condition is continuously changes between clear, cloudy, and hazy. Obviously, camera vision is obscured or even blocked by haze. Another problem is that airlight source is hard to estimate because the lake color tends to be brighter in clear conditions. In this paper, a dehazing technique is proposed based on color attenuation prior and contrast enhancement. In contrast enhancement, the transmission map was enhanced using adaptive gamma correction. Our data were analyzed using referenceless fog density estimation (FADE). Our experimental results give the best result when it comes to fog density (by 1.60912 density) compared to previous algorithms.","PeriodicalId":392163,"journal":{"name":"International Review on Computers and Software","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116180771","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 : 2017-01-31DOI: 10.15866/irecos.v12i1.10928
P. Reji, V. Dharun
In this paper, a coercive and dynamic Automatic Vehicle Number Plate Recognition (AVNPR) scheme is obtained, a throng supervision structure able to detect Indian license plates; it is a cardinal procedure in Intelligent Transportation Systems (ITS). The progression of detection and identification of License Plates in this proposed system is divided in four sections: Image Pre-processing, License Plate Localization, Character Segmentation and Character Recognition. A Feed Forward Back-propagation Neural network (FFBN) Classifier is engaged for this particular system for License Plate exposure and features mining of License Plate characters. The outcomes demonstrate that the proposed system can successfully distinguish and identify License Plates even in problematical surroundings. A superior entitlement of accurateness has been received for the implication of this method and it is confirmed to be 92.13% for the withdrawal of License Plate area and 90.55% identifications of License Plate characters with greater concert than conventional approaches. The planned structure has been put into practice in MATLAB.
{"title":"Design and Implementation of a Vehicle License Plate Characters Recognition System based on FFBN Classifier","authors":"P. Reji, V. Dharun","doi":"10.15866/irecos.v12i1.10928","DOIUrl":"https://doi.org/10.15866/irecos.v12i1.10928","url":null,"abstract":"In this paper, a coercive and dynamic Automatic Vehicle Number Plate Recognition (AVNPR) scheme is obtained, a throng supervision structure able to detect Indian license plates; it is a cardinal procedure in Intelligent Transportation Systems (ITS). The progression of detection and identification of License Plates in this proposed system is divided in four sections: Image Pre-processing, License Plate Localization, Character Segmentation and Character Recognition. A Feed Forward Back-propagation Neural network (FFBN) Classifier is engaged for this particular system for License Plate exposure and features mining of License Plate characters. The outcomes demonstrate that the proposed system can successfully distinguish and identify License Plates even in problematical surroundings. A superior entitlement of accurateness has been received for the implication of this method and it is confirmed to be 92.13% for the withdrawal of License Plate area and 90.55% identifications of License Plate characters with greater concert than conventional approaches. The planned structure has been put into practice in MATLAB.","PeriodicalId":392163,"journal":{"name":"International Review on Computers and Software","volume":"95 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114356306","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 : 2016-12-31DOI: 10.15866/irecos.v11i12.10922
F. R. Zakani, K. Arhid, Mohcine Bouksim, M. Aboulfatah, T. Gadi
{"title":"A New Evaluation Method for Mesh Segmentation Based on the Levenshtein Distance","authors":"F. R. Zakani, K. Arhid, Mohcine Bouksim, M. Aboulfatah, T. Gadi","doi":"10.15866/irecos.v11i12.10922","DOIUrl":"https://doi.org/10.15866/irecos.v11i12.10922","url":null,"abstract":"","PeriodicalId":392163,"journal":{"name":"International Review on Computers and Software","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129209191","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 : 2016-12-31DOI: 10.15866/IRECOS.V11I12.10978
N. Shribala, P. Srihari, B. C. Jinaga
ICT (Information and Communication Technology) trends are fast emerging and globally leading to the substantial demand of spectrum channels used for wireless networks. Cognitive Radio (CR) is an emerging technology solution that shall work on dynamic spectrum channel allocation. In cognitive radio ad hoc networks (CRAN), it is often difficult to establish the path among nodes with direct channel. Hence it is obvious to establish the path through the set of channels in sequence. The constraint is quality of service (QoS). Path establishment by the multiple channels in sequence needs a dynamic channel assignment for ensuring an optimum utilization of the available resources, whilst minimizing the interference in a network. In this paper, the emphasis is on Multichannel transmission Path with optimal QoS fitness for Cognitive Radio Networks. The proposed model is called QoS aware Multi-Channel Path (QMCP) discovery for end-to-end data transmission over CRAN. The QMCP performs the evolutions using adaptive genetic algorithm on the initial multichannel paths discovered in order to obtain the best fit path. The QoS metrics defined in our earlier contribution are used in fitness function. Results from the study reflect the robustness of the proposed model which could certainly impact the quality of channel assignment in CRNs. Since the adaptive genetic algorithm is used, the process complexity and completion time of the QMCP are also assessed.
{"title":"QMCP: QoS Aware Multi-Channel Path Discovery for End to End Data Transmission Over Cognitive Radio Ad Hoc Networks","authors":"N. Shribala, P. Srihari, B. C. Jinaga","doi":"10.15866/IRECOS.V11I12.10978","DOIUrl":"https://doi.org/10.15866/IRECOS.V11I12.10978","url":null,"abstract":"ICT (Information and Communication Technology) trends are fast emerging and globally leading to the substantial demand of spectrum channels used for wireless networks. Cognitive Radio (CR) is an emerging technology solution that shall work on dynamic spectrum channel allocation. In cognitive radio ad hoc networks (CRAN), it is often difficult to establish the path among nodes with direct channel. Hence it is obvious to establish the path through the set of channels in sequence. The constraint is quality of service (QoS). Path establishment by the multiple channels in sequence needs a dynamic channel assignment for ensuring an optimum utilization of the available resources, whilst minimizing the interference in a network. In this paper, the emphasis is on Multichannel transmission Path with optimal QoS fitness for Cognitive Radio Networks. The proposed model is called QoS aware Multi-Channel Path (QMCP) discovery for end-to-end data transmission over CRAN. The QMCP performs the evolutions using adaptive genetic algorithm on the initial multichannel paths discovered in order to obtain the best fit path. The QoS metrics defined in our earlier contribution are used in fitness function. Results from the study reflect the robustness of the proposed model which could certainly impact the quality of channel assignment in CRNs. Since the adaptive genetic algorithm is used, the process complexity and completion time of the QMCP are also assessed.","PeriodicalId":392163,"journal":{"name":"International Review on Computers and Software","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124661062","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 : 2016-12-31DOI: 10.15866/IRECOS.V11I12.10915
A. Tenriawaru, A. Djunaidy, D. Siahaan
{"title":"Mapping Metric Between Meaningful Learning Characteristics and Moodle Activities","authors":"A. Tenriawaru, A. Djunaidy, D. Siahaan","doi":"10.15866/IRECOS.V11I12.10915","DOIUrl":"https://doi.org/10.15866/IRECOS.V11I12.10915","url":null,"abstract":"","PeriodicalId":392163,"journal":{"name":"International Review on Computers and Software","volume":"109 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134437979","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 : 2016-12-31DOI: 10.15866/IRECOS.V11I12.9108
M. A. Hadidi, Y. Ibrahim, V. Lakhno, A. Korchenko, Аnna Tereshchuk, A. Pereverzev
{"title":"Intelligent Systems for Monitoring and Recognition of Cyber Attacks on Information and Communication Systems of Transport","authors":"M. A. Hadidi, Y. Ibrahim, V. Lakhno, A. Korchenko, Аnna Tereshchuk, A. Pereverzev","doi":"10.15866/IRECOS.V11I12.9108","DOIUrl":"https://doi.org/10.15866/IRECOS.V11I12.9108","url":null,"abstract":"","PeriodicalId":392163,"journal":{"name":"International Review on Computers and Software","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134333038","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 : 2016-12-31DOI: 10.15866/IRECOS.V11I12.10579
Kamel Ghanem Ghalem, F. Hendel
In this paper, an efficient method that allows us to authenticate individuals from both-eye images using feature level fusion and score level fusion is presented. The proposed method consists of three main steps: In the first one, the iris images are segmented in order to extract the iris disc. The segmented images are normalized by Daugman rubber sheet model. In the second step, the normalized images are analyzed by a bench of two 1D Log-Gabor filters to extract the texture characteristics. The encoding is realized with a phase of quantization developed by J. Daugman to generate the binary iris templates. In the third step, feature level fusion is applied by concatenation of both binary irises templates and score level fusion is utilized using Dempster Shafer rule. For the authentication and the similarity measurement between both binary irises templates, the hamming distances are used with a previously calculated threshold. The proposal method using two fusion techniques has been tested on a subset of iris database CASIA-IrisV3-Interval. The proposal method using score level fusion based on Dempster Shafer rule shows better performance with accuracy of 99.97%, FPR of 0% FNR of 4.49%, EER of 1.4% and processing time of 15.39s for one iris image.
{"title":"Individuals Authentication from Both-Eye Images Using Feature Level Fusion and Score Level Fusion","authors":"Kamel Ghanem Ghalem, F. Hendel","doi":"10.15866/IRECOS.V11I12.10579","DOIUrl":"https://doi.org/10.15866/IRECOS.V11I12.10579","url":null,"abstract":"In this paper, an efficient method that allows us to authenticate individuals from both-eye images using feature level fusion and score level fusion is presented. The proposed method consists of three main steps: In the first one, the iris images are segmented in order to extract the iris disc. The segmented images are normalized by Daugman rubber sheet model. In the second step, the normalized images are analyzed by a bench of two 1D Log-Gabor filters to extract the texture characteristics. The encoding is realized with a phase of quantization developed by J. Daugman to generate the binary iris templates. In the third step, feature level fusion is applied by concatenation of both binary irises templates and score level fusion is utilized using Dempster Shafer rule. For the authentication and the similarity measurement between both binary irises templates, the hamming distances are used with a previously calculated threshold. The proposal method using two fusion techniques has been tested on a subset of iris database CASIA-IrisV3-Interval. The proposal method using score level fusion based on Dempster Shafer rule shows better performance with accuracy of 99.97%, FPR of 0% FNR of 4.49%, EER of 1.4% and processing time of 15.39s for one iris image.","PeriodicalId":392163,"journal":{"name":"International Review on Computers and Software","volume":"94 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125711259","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 : 2016-12-31DOI: 10.15866/IRECOS.V11I12.10624
Sreejith Vidhyadharran, Prateek Khandelwal, L. Gudino, K. Anupama
{"title":"Energy Efficient Mobile MAC Protocol with Mobility Vector for Neighbor Selection in Wireless Sensor Networks","authors":"Sreejith Vidhyadharran, Prateek Khandelwal, L. Gudino, K. Anupama","doi":"10.15866/IRECOS.V11I12.10624","DOIUrl":"https://doi.org/10.15866/IRECOS.V11I12.10624","url":null,"abstract":"","PeriodicalId":392163,"journal":{"name":"International Review on Computers and Software","volume":"29 2","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131491535","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 : 2016-12-31DOI: 10.15866/IRECOS.V11I12.10414
Khadidja Belbachir, H. Belbachir
{"title":"New Algorithms for Data Mining on Grid Computing","authors":"Khadidja Belbachir, H. Belbachir","doi":"10.15866/IRECOS.V11I12.10414","DOIUrl":"https://doi.org/10.15866/IRECOS.V11I12.10414","url":null,"abstract":"","PeriodicalId":392163,"journal":{"name":"International Review on Computers and Software","volume":"202 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134310420","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 : 2016-12-31DOI: 10.15866/IRECOS.V11I12.10964
A. Bendahmane, A. Benyettou
{"title":"Learning to Generate Optimized Term Weighting for Web Documents Classification - A Parallel Mimetic Approach Based on Support Vector Machines","authors":"A. Bendahmane, A. Benyettou","doi":"10.15866/IRECOS.V11I12.10964","DOIUrl":"https://doi.org/10.15866/IRECOS.V11I12.10964","url":null,"abstract":"","PeriodicalId":392163,"journal":{"name":"International Review on Computers and Software","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133124001","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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