Pub Date : 2012-07-26DOI: 10.1109/ICCCNT.2012.6396093
N. V. Anil Kumar, A. Thomas
Improving network lifetime is the fundamental challenge of wireless sensor networks. One possible solution consists in making use of mobile sinks. Sink mobility along a constrained path can improve the energy efficiency in wireless sensor networks. However, due to the path constraint, a mobile sink with constant speed has limited communication time to collect data from the sensor nodes deployed randomly. This poses significant challenges in jointly improving the amount of data collected and reducing the energy consumption. This paper propose a novel data collection scheme, called the Maximum Amount Shortest Path (MASP) using Improved Ant Colony Optimization, to address this issue, that increases network throughput as well as conserves energy by optimizing the assignment of sensor nodes. MASP is formulated as an integer linear programming problem and then solved with the help of improved ant colony optimization. Zone based partition is applied to implement the MASP scheme. The residual energy of each node is calculated and the optimal path is selected by considering the shortest path, residual energy, channel noise, and delay. This approach is validated through simulation experiments using NS2.
{"title":"Energy efficiency and network lifetime maximization in wireless sensor networks using Improved Ant Colony Optimization","authors":"N. V. Anil Kumar, A. Thomas","doi":"10.1109/ICCCNT.2012.6396093","DOIUrl":"https://doi.org/10.1109/ICCCNT.2012.6396093","url":null,"abstract":"Improving network lifetime is the fundamental challenge of wireless sensor networks. One possible solution consists in making use of mobile sinks. Sink mobility along a constrained path can improve the energy efficiency in wireless sensor networks. However, due to the path constraint, a mobile sink with constant speed has limited communication time to collect data from the sensor nodes deployed randomly. This poses significant challenges in jointly improving the amount of data collected and reducing the energy consumption. This paper propose a novel data collection scheme, called the Maximum Amount Shortest Path (MASP) using Improved Ant Colony Optimization, to address this issue, that increases network throughput as well as conserves energy by optimizing the assignment of sensor nodes. MASP is formulated as an integer linear programming problem and then solved with the help of improved ant colony optimization. Zone based partition is applied to implement the MASP scheme. The residual energy of each node is calculated and the optimal path is selected by considering the shortest path, residual energy, channel noise, and delay. This approach is validated through simulation experiments using NS2.","PeriodicalId":364589,"journal":{"name":"2012 Third International Conference on Computing, Communication and Networking Technologies (ICCCNT'12)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122662397","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 : 2012-07-26DOI: 10.1109/ICCCNT.2012.6395927
A. Sharma, A. Roy, S. Ghosal, R. Chaki, U. Bhattacharya
Mobile Stations (MSs), in real-world systems, are not evenly distributed across cells. Thus, MSs in a hot cell are affected by the load imbalance and might unable to get services. Load balancing became one of the most active and emerging fields of research in Cellular Network. In order to balance the load among different cells, it is needed to transfer the over-loaded traffic from hot cells to neighbouring cooler ones. Various dynamic load balancing schemes to deal with the unbalanced traffic problem are already proposed. In this paper we have reviewed various techniques of load balancing in cellular network. We have also presented two comparison tables for the reviewed schemes. This work would help look at a glance to the previous works done in the area of Load Balancing in Cellular Networks.
{"title":"Load balancing in Cellular Network: A review","authors":"A. Sharma, A. Roy, S. Ghosal, R. Chaki, U. Bhattacharya","doi":"10.1109/ICCCNT.2012.6395927","DOIUrl":"https://doi.org/10.1109/ICCCNT.2012.6395927","url":null,"abstract":"Mobile Stations (MSs), in real-world systems, are not evenly distributed across cells. Thus, MSs in a hot cell are affected by the load imbalance and might unable to get services. Load balancing became one of the most active and emerging fields of research in Cellular Network. In order to balance the load among different cells, it is needed to transfer the over-loaded traffic from hot cells to neighbouring cooler ones. Various dynamic load balancing schemes to deal with the unbalanced traffic problem are already proposed. In this paper we have reviewed various techniques of load balancing in cellular network. We have also presented two comparison tables for the reviewed schemes. This work would help look at a glance to the previous works done in the area of Load Balancing in Cellular Networks.","PeriodicalId":364589,"journal":{"name":"2012 Third International Conference on Computing, Communication and Networking Technologies (ICCCNT'12)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122914974","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 : 2012-07-26DOI: 10.1109/ICCCNT.2012.6395974
R. K. Bawa, R. Singh
Grid technologies are emerging as the next generation of distributed computing, allowing the aggregation of heterogeneous resources that are geographically distributed. The heterogeneous nature of the grid makes it more vulnerable to faults which lead to either the failure of the job or delay in completing the execution of the job. Checkpointing is one of the many fault tolerance techniques which are used to make Grid more efficient and reliable. In this paper we have developed an application checkpointing based fault tolerance technique for Alchemi based Grid environment. In this technique application threads generate their checkpoints and store them in the checkpoint table at the manager node. In case a thread fails checkpoint of the corresponding thread is used to resume the execution from the point of failure. This technique introduces a slight overhead in fault free situations but very effective in case of a node failure. Increased checkpoint frequency improves job's resuming capability but also increases the overhead of generating and storing checkpoints which results in increased processing time of the job.
{"title":"Application checkpointing in grid environment with improved checkpoint reliability through replication","authors":"R. K. Bawa, R. Singh","doi":"10.1109/ICCCNT.2012.6395974","DOIUrl":"https://doi.org/10.1109/ICCCNT.2012.6395974","url":null,"abstract":"Grid technologies are emerging as the next generation of distributed computing, allowing the aggregation of heterogeneous resources that are geographically distributed. The heterogeneous nature of the grid makes it more vulnerable to faults which lead to either the failure of the job or delay in completing the execution of the job. Checkpointing is one of the many fault tolerance techniques which are used to make Grid more efficient and reliable. In this paper we have developed an application checkpointing based fault tolerance technique for Alchemi based Grid environment. In this technique application threads generate their checkpoints and store them in the checkpoint table at the manager node. In case a thread fails checkpoint of the corresponding thread is used to resume the execution from the point of failure. This technique introduces a slight overhead in fault free situations but very effective in case of a node failure. Increased checkpoint frequency improves job's resuming capability but also increases the overhead of generating and storing checkpoints which results in increased processing time of the job.","PeriodicalId":364589,"journal":{"name":"2012 Third International Conference on Computing, Communication and Networking Technologies (ICCCNT'12)","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127564679","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 : 2012-07-26DOI: 10.1109/ICCCNT.2012.6395880
V. S. Dessai, M. P. Arakeri, G. Ram Mohana Reddy
Medical image segmentation is nowadays at the core of medical image analysis and supports computer-aided diagnosis, surgical planning, intra-operative guidance or postoperative assessment. Large amounts of research efforts have been made in developing effective brain MR (magnetic resonance) image tumor segmentation methods in the past years. However algorithms proposed so far are time consuming because it involves lot of mathematical computations. Also serial segmentation of multiple MRI slices (usually required for 3D visualization) takes exponential time. This results in need for improvement in performance as far as the time complexity is concerned. This paper proposes a methodology that incorporates the K-means clustering and morphological operation for parallel segmentation of multiple MRI slices corresponding to single patient. Segmentation of multiple MRI slices for tumor extraction plays major role in 3D (Three Dimensional) visualization and serves as an input for the same. The proposed framework follows SIMD (Single Instruction Multiple Data) model and since the segmentation of individual slice is independent of each other and can be performed in parallel and multithreading definitely speeds up the entire process. Also the framework does not involve any kind of inter-process communication thus the time is saved here as well.
{"title":"A parallel segmentation of brain tumor from magnetic resonance images","authors":"V. S. Dessai, M. P. Arakeri, G. Ram Mohana Reddy","doi":"10.1109/ICCCNT.2012.6395880","DOIUrl":"https://doi.org/10.1109/ICCCNT.2012.6395880","url":null,"abstract":"Medical image segmentation is nowadays at the core of medical image analysis and supports computer-aided diagnosis, surgical planning, intra-operative guidance or postoperative assessment. Large amounts of research efforts have been made in developing effective brain MR (magnetic resonance) image tumor segmentation methods in the past years. However algorithms proposed so far are time consuming because it involves lot of mathematical computations. Also serial segmentation of multiple MRI slices (usually required for 3D visualization) takes exponential time. This results in need for improvement in performance as far as the time complexity is concerned. This paper proposes a methodology that incorporates the K-means clustering and morphological operation for parallel segmentation of multiple MRI slices corresponding to single patient. Segmentation of multiple MRI slices for tumor extraction plays major role in 3D (Three Dimensional) visualization and serves as an input for the same. The proposed framework follows SIMD (Single Instruction Multiple Data) model and since the segmentation of individual slice is independent of each other and can be performed in parallel and multithreading definitely speeds up the entire process. Also the framework does not involve any kind of inter-process communication thus the time is saved here as well.","PeriodicalId":364589,"journal":{"name":"2012 Third International Conference on Computing, Communication and Networking Technologies (ICCCNT'12)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127661148","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 : 2012-07-26DOI: 10.1109/ICCCNT.2012.6395950
S. Parija, P. K. Sahu, S. S. Singh
Speech enhancement aims to improve speech quality by using various algorithms. The main objective of enhancement is to improvement in intelligibility and overall perceptual quality of degraded speech signal using audio signal processing techniques. In the field of speech enhancement, enhancing of speech means degraded by noise in its wide range of applications such as mobile phones, VoIP, teleconferencing systems etc. In general there are three different methods used to estimate speech intelligibility. Namely, Speech Intelligibility Index (SII), Speech Transmission Index (STI) and Articulation Index (AI). Here it is proposed that SII is most robust physical measure and the comparison between Speech Intelligibility index in presence of stationary noise (White Gaussian Noise) and non-stationary noise (Speech noise) is done. Simulation result shows that SII is better in presence of non-stationary noise (a female voice of sampling frequency 16 KHz). Here two wideband speech signals are considered for performance evaluation since it brings the improvement over traditional narrowband such as increases the intelligibility and enables the spatial auditory displays etc. The speech signal are generated and simulated with the MATLAB environment. The real time speech signals are recorded with the help of acoustic sensor present inside the microphone.
{"title":"Speech enhancement by speech intelligibility index in sensor network","authors":"S. Parija, P. K. Sahu, S. S. Singh","doi":"10.1109/ICCCNT.2012.6395950","DOIUrl":"https://doi.org/10.1109/ICCCNT.2012.6395950","url":null,"abstract":"Speech enhancement aims to improve speech quality by using various algorithms. The main objective of enhancement is to improvement in intelligibility and overall perceptual quality of degraded speech signal using audio signal processing techniques. In the field of speech enhancement, enhancing of speech means degraded by noise in its wide range of applications such as mobile phones, VoIP, teleconferencing systems etc. In general there are three different methods used to estimate speech intelligibility. Namely, Speech Intelligibility Index (SII), Speech Transmission Index (STI) and Articulation Index (AI). Here it is proposed that SII is most robust physical measure and the comparison between Speech Intelligibility index in presence of stationary noise (White Gaussian Noise) and non-stationary noise (Speech noise) is done. Simulation result shows that SII is better in presence of non-stationary noise (a female voice of sampling frequency 16 KHz). Here two wideband speech signals are considered for performance evaluation since it brings the improvement over traditional narrowband such as increases the intelligibility and enables the spatial auditory displays etc. The speech signal are generated and simulated with the MATLAB environment. The real time speech signals are recorded with the help of acoustic sensor present inside the microphone.","PeriodicalId":364589,"journal":{"name":"2012 Third International Conference on Computing, Communication and Networking Technologies (ICCCNT'12)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133679343","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 : 2012-07-26DOI: 10.1109/ICCCNT.2012.6396032
S. A. Rehman, R. Kumar, M. Rao
In this paper various adaptive filter based algorithms that can be applied to ECG signal in order to remove various artifacts from them are presented. The goal of the paper is to show the comparison based on signal to noise ratio of all adaptive filter algorithms used for the analysis of ECG signals with Baseline wander noise. Simulation studies shows that the proposed novel algorithms like NLMS, SRLMS and DNLMS based on adaptive systems present better performances compared to existing realizations LMS, DLMS and NSRLMS based procedures in terms of signal to noise ratio.
{"title":"Performance comparison of various adaptive filter algorithms for ECG signal enhancement and baseline wander removal","authors":"S. A. Rehman, R. Kumar, M. Rao","doi":"10.1109/ICCCNT.2012.6396032","DOIUrl":"https://doi.org/10.1109/ICCCNT.2012.6396032","url":null,"abstract":"In this paper various adaptive filter based algorithms that can be applied to ECG signal in order to remove various artifacts from them are presented. The goal of the paper is to show the comparison based on signal to noise ratio of all adaptive filter algorithms used for the analysis of ECG signals with Baseline wander noise. Simulation studies shows that the proposed novel algorithms like NLMS, SRLMS and DNLMS based on adaptive systems present better performances compared to existing realizations LMS, DLMS and NSRLMS based procedures in terms of signal to noise ratio.","PeriodicalId":364589,"journal":{"name":"2012 Third International Conference on Computing, Communication and Networking Technologies (ICCCNT'12)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132212565","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 : 2012-07-26DOI: 10.1109/ICCCNT.2012.6395998
S. P. Ngayarkanni, N. Kamal, V. Thavavel
Breast cancer is one of the most common forms of cancer in women. In order to reduce the death rate , early detection of cancerous regions in mammogram images is needed. The existing system is not so accurate and it is time consuming. The Proposed system is mainly used for automatic segmentation of the mammogram images and classifies them as benign, malignant or normal based on the decision tree ID3 algorithm. A hybrid method of data mining technique is used to predict the texture features which play a vital role in classification. The sensitivity, the specificity, positive prediction value and negative prediction value of the proposed algorithm were determined and compared with the existing algorithms. The size and the stages of the tumor is detected using the ellipsoid volume formula which is calculated over the segmented region. Automatic classification of the mammogram MRI images is done through three layered ANN .The weights are adjusted based on the rule extracted from ID3 algorithm .Both qualitative and quantitative methods are used to detect the accuracy of the proposed system.The sensitivity, the specificity, positive prediction value and negative prediction value of the proposed algorithm accounts to 99.78%, 99.9%, 94% and 98.5% which rates very high when compared to the existing algorithms. This paper focuses on the comparative analysis of the existing methods and the proposed technique in terms of sensitivity, specificity, accuracy, time consumption and ROC.
{"title":"Automatic detection and classification of cancerous masses in mammogram","authors":"S. P. Ngayarkanni, N. Kamal, V. Thavavel","doi":"10.1109/ICCCNT.2012.6395998","DOIUrl":"https://doi.org/10.1109/ICCCNT.2012.6395998","url":null,"abstract":"Breast cancer is one of the most common forms of cancer in women. In order to reduce the death rate , early detection of cancerous regions in mammogram images is needed. The existing system is not so accurate and it is time consuming. The Proposed system is mainly used for automatic segmentation of the mammogram images and classifies them as benign, malignant or normal based on the decision tree ID3 algorithm. A hybrid method of data mining technique is used to predict the texture features which play a vital role in classification. The sensitivity, the specificity, positive prediction value and negative prediction value of the proposed algorithm were determined and compared with the existing algorithms. The size and the stages of the tumor is detected using the ellipsoid volume formula which is calculated over the segmented region. Automatic classification of the mammogram MRI images is done through three layered ANN .The weights are adjusted based on the rule extracted from ID3 algorithm .Both qualitative and quantitative methods are used to detect the accuracy of the proposed system.The sensitivity, the specificity, positive prediction value and negative prediction value of the proposed algorithm accounts to 99.78%, 99.9%, 94% and 98.5% which rates very high when compared to the existing algorithms. This paper focuses on the comparative analysis of the existing methods and the proposed technique in terms of sensitivity, specificity, accuracy, time consumption and ROC.","PeriodicalId":364589,"journal":{"name":"2012 Third International Conference on Computing, Communication and Networking Technologies (ICCCNT'12)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134366493","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 : 2012-07-26DOI: 10.1109/ICCCNT.2012.6396019
T. R. Sivapriya, A. Kamal, V. Thavavel
The objective of this study is to investigate the use of LSSVM (Least Square Support Vector Machine) trained with Chaotic PSO (Particle Swarm Optimization) for distinguishing different levels of Dementia from brain MRI. The availability of an effective method that is more objective than human readers can potentially lead to more reliable and reproducible dementia diagnostic procedures. The proposed scheme consists of several steps including feature extraction, feature selection and classification. This research paper proposes an intelligent classification technique to identify normal and demented patients using LSSVM. The manual interpretation of large volumes of brain MRI may lead to incomplete diagnosis. Hence the LSSVM approach is trained with multiple biomarkers to facilitate effective, accurate classification which is a requirement of the hour. SVM-PSO, LS-SVM-PSO classifiers are compared with LS-SVM trained by Chaotic PSO. LS-SVM-Chaotic PSO yields 100% accurate results and outperforms other classifiers in terms of sensitivity, specificity and accuracy in this analysis.
{"title":"Automated classification of MRI based on hybrid Least Square Support Vector Machine and Chaotic PSO","authors":"T. R. Sivapriya, A. Kamal, V. Thavavel","doi":"10.1109/ICCCNT.2012.6396019","DOIUrl":"https://doi.org/10.1109/ICCCNT.2012.6396019","url":null,"abstract":"The objective of this study is to investigate the use of LSSVM (Least Square Support Vector Machine) trained with Chaotic PSO (Particle Swarm Optimization) for distinguishing different levels of Dementia from brain MRI. The availability of an effective method that is more objective than human readers can potentially lead to more reliable and reproducible dementia diagnostic procedures. The proposed scheme consists of several steps including feature extraction, feature selection and classification. This research paper proposes an intelligent classification technique to identify normal and demented patients using LSSVM. The manual interpretation of large volumes of brain MRI may lead to incomplete diagnosis. Hence the LSSVM approach is trained with multiple biomarkers to facilitate effective, accurate classification which is a requirement of the hour. SVM-PSO, LS-SVM-PSO classifiers are compared with LS-SVM trained by Chaotic PSO. LS-SVM-Chaotic PSO yields 100% accurate results and outperforms other classifiers in terms of sensitivity, specificity and accuracy in this analysis.","PeriodicalId":364589,"journal":{"name":"2012 Third International Conference on Computing, Communication and Networking Technologies (ICCCNT'12)","volume":"26 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132434131","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 : 2012-07-26DOI: 10.1109/ICCCNT.2012.6396075
R. Ramkumar, S. Arumugam
Goal of the proposed iris recognition is to recognize human identity through the textural characteristics of one's iris muscular patterns. Even though eye color is dependent on heredity, in contrast to this, iris is independent and uncorrelated even for twins. Out of various biometrics such as finger and hand geometry, face, ear and voice recognition, iris recognition has been acknowledged as one of the most accurate biometric modalities because of its high recognition rate. In this proposed iris recognition method, pupil localization is done by using negative function and four neighbours method so that irrespective of pupil's contour, either circle or ellipse, the pupil's boundary is detected accurately. For iris outer boundary detection, contrast enhancement, special wedges and thresholding techniques are used to isolate the specific iris regions without eyelid and eyelash occlusions. Now the resultant iris portion alone is transformed into polar coordinate system for normalization process. Histogram equalization technique is used for enhancing the normalized iris image. For feature extraction and matching process, cumulative sum-based change analysis and hamming distance are employed. When compared with the existing algorithms, this proposed algorithm is robust, accurate and also has low computational time and complexity.
{"title":"A novel iris recognition algorithm","authors":"R. Ramkumar, S. Arumugam","doi":"10.1109/ICCCNT.2012.6396075","DOIUrl":"https://doi.org/10.1109/ICCCNT.2012.6396075","url":null,"abstract":"Goal of the proposed iris recognition is to recognize human identity through the textural characteristics of one's iris muscular patterns. Even though eye color is dependent on heredity, in contrast to this, iris is independent and uncorrelated even for twins. Out of various biometrics such as finger and hand geometry, face, ear and voice recognition, iris recognition has been acknowledged as one of the most accurate biometric modalities because of its high recognition rate. In this proposed iris recognition method, pupil localization is done by using negative function and four neighbours method so that irrespective of pupil's contour, either circle or ellipse, the pupil's boundary is detected accurately. For iris outer boundary detection, contrast enhancement, special wedges and thresholding techniques are used to isolate the specific iris regions without eyelid and eyelash occlusions. Now the resultant iris portion alone is transformed into polar coordinate system for normalization process. Histogram equalization technique is used for enhancing the normalized iris image. For feature extraction and matching process, cumulative sum-based change analysis and hamming distance are employed. When compared with the existing algorithms, this proposed algorithm is robust, accurate and also has low computational time and complexity.","PeriodicalId":364589,"journal":{"name":"2012 Third International Conference on Computing, Communication and Networking Technologies (ICCCNT'12)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134580317","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 : 2012-07-26DOI: 10.1109/ICCCNT.2012.6396005
R. Thiruvengadathan, S. Srikanth
In this paper we analyze the performance of different channel estimators under different antenna correlation conditions. This analysis is performed for various spatial multiplexing techniques considered in 3GPP Long term evolution (LTE) Release 8 (R8) using extensive simulations. By considering the LTE downlink system parameters and the LTE channel model, we measure the performance of channel estimators. Finally we present the performance of channel estimation on the performance of precoding in LTE systems.
{"title":"Performance of MIMO channel estimation in LTE downlink","authors":"R. Thiruvengadathan, S. Srikanth","doi":"10.1109/ICCCNT.2012.6396005","DOIUrl":"https://doi.org/10.1109/ICCCNT.2012.6396005","url":null,"abstract":"In this paper we analyze the performance of different channel estimators under different antenna correlation conditions. This analysis is performed for various spatial multiplexing techniques considered in 3GPP Long term evolution (LTE) Release 8 (R8) using extensive simulations. By considering the LTE downlink system parameters and the LTE channel model, we measure the performance of channel estimators. Finally we present the performance of channel estimation on the performance of precoding in LTE systems.","PeriodicalId":364589,"journal":{"name":"2012 Third International Conference on Computing, Communication and Networking Technologies (ICCCNT'12)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-07-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131561390","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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