Pub Date : 2016-07-25DOI: 10.1109/JEC-ECC.2016.7518987
A. Mostafa, N. Soliman, Mohamoud Abdalluh, F. A. Abd El-Samie
This paper introduces a good technique for the utilization of cancelable features for speaker identification. This technique depends on the use of encrypted features extracted from speech signals for identification. The encrypted features are obtained through convolution with random kernels. The proposed speaker identification system using cancelable features has been evaluated under the effect of Additive White Gaussian Noise (AWGN). Some quality metrics such as Log-Likelihood Ratio (LLR), Spectral Distortion (SD), and auto correlation have been used to assess the performance of the speaker identification system.
{"title":"Effect of voice features cancellation in speaker identification system","authors":"A. Mostafa, N. Soliman, Mohamoud Abdalluh, F. A. Abd El-Samie","doi":"10.1109/JEC-ECC.2016.7518987","DOIUrl":"https://doi.org/10.1109/JEC-ECC.2016.7518987","url":null,"abstract":"This paper introduces a good technique for the utilization of cancelable features for speaker identification. This technique depends on the use of encrypted features extracted from speech signals for identification. The encrypted features are obtained through convolution with random kernels. The proposed speaker identification system using cancelable features has been evaluated under the effect of Additive White Gaussian Noise (AWGN). Some quality metrics such as Log-Likelihood Ratio (LLR), Spectral Distortion (SD), and auto correlation have been used to assess the performance of the speaker identification system.","PeriodicalId":362288,"journal":{"name":"2016 Fourth International Japan-Egypt Conference on Electronics, Communications and Computers (JEC-ECC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114124373","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 : 2016-07-25DOI: 10.1109/JEC-ECC.2016.7518956
M. Elhadad, El-Sayed M. El-Rabaie, M. Abd-Elnaby
In this paper we introduce and asses the performance of a new scheduling algorithm based on Earliest Due Date (EDD) mechanism. Our proposed scheduling algorithm enhances the performance of Real-Time (RT) flows such as video and Voice Over Internet Protocol (VOIP) in Long Term Evolution (LTE) cellular networks especially in downlink. The proposed scheduling scheme provides the lowest Packet Loss Ratio (PLR) for RT multimedia services, this can be achieved by taking the expiration time of the head of line packets of users' queues into account. Also, the proposed scheduling algorithm which we call Modified-Earliest Due Date (M-EDD), achieves higher bitrate for the RT applications. Especially for the video traffic, results have remarkably demonstrated that the M-EDD scheduling algorithm has the capacity to clearly outperform the conventional scheduling schemes.
{"title":"Resource allocation for Real-Time services using Earliest Due Date mechanism in LTE networks","authors":"M. Elhadad, El-Sayed M. El-Rabaie, M. Abd-Elnaby","doi":"10.1109/JEC-ECC.2016.7518956","DOIUrl":"https://doi.org/10.1109/JEC-ECC.2016.7518956","url":null,"abstract":"In this paper we introduce and asses the performance of a new scheduling algorithm based on Earliest Due Date (EDD) mechanism. Our proposed scheduling algorithm enhances the performance of Real-Time (RT) flows such as video and Voice Over Internet Protocol (VOIP) in Long Term Evolution (LTE) cellular networks especially in downlink. The proposed scheduling scheme provides the lowest Packet Loss Ratio (PLR) for RT multimedia services, this can be achieved by taking the expiration time of the head of line packets of users' queues into account. Also, the proposed scheduling algorithm which we call Modified-Earliest Due Date (M-EDD), achieves higher bitrate for the RT applications. Especially for the video traffic, results have remarkably demonstrated that the M-EDD scheduling algorithm has the capacity to clearly outperform the conventional scheduling schemes.","PeriodicalId":362288,"journal":{"name":"2016 Fourth International Japan-Egypt Conference on Electronics, Communications and Computers (JEC-ECC)","volume":"63 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116538393","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 : 2016-07-25DOI: 10.1109/JEC-ECC.2016.7518967
Nagwa M. Aboelenein, K. Amin, Mina I. S. Ibrahim, M. Hadhoud
Speaker identification identifies the speaker among a set of users by matching against a set of voiceprints. In speaker identification, the identification time depends on the number of feature vectors, their dimensionality and the number of speakers. In this paper, text independent speaker identification model is developed by taking in MFCCs with VQ to obtain pressed feature vectors without losing much information, and the numbers of speakers are reduced in the test by gender detection algorithm. Gaussian Mixture Model (GMM) is used a modeling technique. Results show that proposed approach always yields better improvements in accuracy and brings almost 50% reduces in time processing.
{"title":"Improved text-independent speaker identification system for real time applications","authors":"Nagwa M. Aboelenein, K. Amin, Mina I. S. Ibrahim, M. Hadhoud","doi":"10.1109/JEC-ECC.2016.7518967","DOIUrl":"https://doi.org/10.1109/JEC-ECC.2016.7518967","url":null,"abstract":"Speaker identification identifies the speaker among a set of users by matching against a set of voiceprints. In speaker identification, the identification time depends on the number of feature vectors, their dimensionality and the number of speakers. In this paper, text independent speaker identification model is developed by taking in MFCCs with VQ to obtain pressed feature vectors without losing much information, and the numbers of speakers are reduced in the test by gender detection algorithm. Gaussian Mixture Model (GMM) is used a modeling technique. Results show that proposed approach always yields better improvements in accuracy and brings almost 50% reduces in time processing.","PeriodicalId":362288,"journal":{"name":"2016 Fourth International Japan-Egypt Conference on Electronics, Communications and Computers (JEC-ECC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129902074","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 : 2016-07-25DOI: 10.1109/JEC-ECC.2016.7518977
A. Atef, M. Atef, M. Abbas, E. Khaled
This paper presents a design and a post layout simulation of a high-sensitivity low-power transimpedance amplifier (TIA) for frequency domain near infrared spectroscopy (FD-NIRS). The TIA consumes 340 μW from a 1.2 V DC supply. This low power is necessary for NIRS device portability. The proposed TIA achieves 104.8 dBΩ transimpedance gain, 50 MHz bandwidth and 15.1 nArms total integrated input noise current for 2 pF off chip photodiode capacitance. The demonstrated TIA is simulated using 130 nm CMOS technology and occupies an area of 0.0012 mm2. Post amplifier stage is presented to increase the total gain. The complete NIRS optical receiver achieves 119.5 dBΩ gain, 49.2 MHz bandwidth, 15.4 nArms total integrated input noise current and consumes 400 μW from a 1.2 V DC supply.
{"title":"High-sensitivity regulated inverter cascode transimpedance amplifier for near infrared spectroscopy","authors":"A. Atef, M. Atef, M. Abbas, E. Khaled","doi":"10.1109/JEC-ECC.2016.7518977","DOIUrl":"https://doi.org/10.1109/JEC-ECC.2016.7518977","url":null,"abstract":"This paper presents a design and a post layout simulation of a high-sensitivity low-power transimpedance amplifier (TIA) for frequency domain near infrared spectroscopy (FD-NIRS). The TIA consumes 340 μW from a 1.2 V DC supply. This low power is necessary for NIRS device portability. The proposed TIA achieves 104.8 dBΩ transimpedance gain, 50 MHz bandwidth and 15.1 nArms total integrated input noise current for 2 pF off chip photodiode capacitance. The demonstrated TIA is simulated using 130 nm CMOS technology and occupies an area of 0.0012 mm2. Post amplifier stage is presented to increase the total gain. The complete NIRS optical receiver achieves 119.5 dBΩ gain, 49.2 MHz bandwidth, 15.4 nArms total integrated input noise current and consumes 400 μW from a 1.2 V DC supply.","PeriodicalId":362288,"journal":{"name":"2016 Fourth International Japan-Egypt Conference on Electronics, Communications and Computers (JEC-ECC)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127107250","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 : 2016-07-25DOI: 10.1109/JEC-ECC.2016.7518961
M. S. Saleh, M. El-Mahlawy, Hossam E. Abou-Bakr Hassan
In this paper, the new testability analysis method of analogue circuits is presented. The observability of parametric faults is evaluated by determining a proper test signal that maximizes the error between the good and the faulty circuit at a target fault. The efficient method to optimize the multi-frequency test set by determining the basis of the decision matrix is presented. The decision matrix is calculated from the frequency set of the test signal, extracted from the testability analysis. This set is ranked by calculating the total fault coverage of each test signal. The analog test problem is formulated as selecting an optimal subset from an initial test set defined in terms of fault coverage and fault separation on a given fault set. The presented method is applied to test some analogue benchmark circuits [1] and compared with previous published testing methods. The results show the superiority of our presented method.
{"title":"New testability analysis and multi-frequency test set compaction method for analogue circuits","authors":"M. S. Saleh, M. El-Mahlawy, Hossam E. Abou-Bakr Hassan","doi":"10.1109/JEC-ECC.2016.7518961","DOIUrl":"https://doi.org/10.1109/JEC-ECC.2016.7518961","url":null,"abstract":"In this paper, the new testability analysis method of analogue circuits is presented. The observability of parametric faults is evaluated by determining a proper test signal that maximizes the error between the good and the faulty circuit at a target fault. The efficient method to optimize the multi-frequency test set by determining the basis of the decision matrix is presented. The decision matrix is calculated from the frequency set of the test signal, extracted from the testability analysis. This set is ranked by calculating the total fault coverage of each test signal. The analog test problem is formulated as selecting an optimal subset from an initial test set defined in terms of fault coverage and fault separation on a given fault set. The presented method is applied to test some analogue benchmark circuits [1] and compared with previous published testing methods. The results show the superiority of our presented method.","PeriodicalId":362288,"journal":{"name":"2016 Fourth International Japan-Egypt Conference on Electronics, Communications and Computers (JEC-ECC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132583918","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 : 2016-07-25DOI: 10.1109/JEC-ECC.2016.7518982
M. Mahfouz, Y. El-Sonbaty, M. Ismail
Symbolic data classification is of great importance in classification of massive high dimensional data that may exist in domains such as bioinformatics and web mining. Feature values (events) of symbolic data are generally not single values, as in the classical case, but rather list of values, intervals or, more generally, distributions. This study proposes a symbolic classification algorithm that uses distinguished variations in the frequency of frequent one and two item-sets extracted from each class sample. The events and events pairs that have enough high support in one class and very low in others are identified. A symbolic profile is built using identified item-sets. Incoming pattern is compared to the profile of each class and the class that achieves maximum similarity with the object to be classified is selected. Experimental study on two standard datasets shows that the proposed algorithm uses a small subset of events pairs in building a profile of each class and is able to achieve a comparable accuracy with less computational complexity compared to variants of the state of the art SVM.
{"title":"SDAF: Symbolic data classification using variations in frequent terms","authors":"M. Mahfouz, Y. El-Sonbaty, M. Ismail","doi":"10.1109/JEC-ECC.2016.7518982","DOIUrl":"https://doi.org/10.1109/JEC-ECC.2016.7518982","url":null,"abstract":"Symbolic data classification is of great importance in classification of massive high dimensional data that may exist in domains such as bioinformatics and web mining. Feature values (events) of symbolic data are generally not single values, as in the classical case, but rather list of values, intervals or, more generally, distributions. This study proposes a symbolic classification algorithm that uses distinguished variations in the frequency of frequent one and two item-sets extracted from each class sample. The events and events pairs that have enough high support in one class and very low in others are identified. A symbolic profile is built using identified item-sets. Incoming pattern is compared to the profile of each class and the class that achieves maximum similarity with the object to be classified is selected. Experimental study on two standard datasets shows that the proposed algorithm uses a small subset of events pairs in building a profile of each class and is able to achieve a comparable accuracy with less computational complexity compared to variants of the state of the art SVM.","PeriodicalId":362288,"journal":{"name":"2016 Fourth International Japan-Egypt Conference on Electronics, Communications and Computers (JEC-ECC)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127445186","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 : 2016-07-21DOI: 10.1109/JEC-ECC.2016.7518968
H. Atallah, A. Abdel-Rahman, K. Yoshitomi, R. Pokharel
In this paper, a new compact tunable microstrip-line fed slot antenna is proposed for interweave cognitive radio (CR) front end systems. The proposed antenna utilized four varactor diodes to control the antenna resonant frequency. The resonant frequency of the antenna can be electronically tuned by changing the effective electrical length of the resonant slot, which is accomplished by employing the varactor diodes inside the slot. Moreover, the simple biasing of the varactor diodes has a small effect on the antenna performance. Simulation results show that the proposed antenna is capable of frequency switching over a tuning range of 0.93 GHz from 1.83 to 2.76 GHz with 40.5 % frequency tuning range. The proposed antenna has a miniaturized size of 25 × 30 × 0.762 mm3.
{"title":"Design of miniaturized reconfigurable slot antenna using varactor diodes for cognitive radio systems","authors":"H. Atallah, A. Abdel-Rahman, K. Yoshitomi, R. Pokharel","doi":"10.1109/JEC-ECC.2016.7518968","DOIUrl":"https://doi.org/10.1109/JEC-ECC.2016.7518968","url":null,"abstract":"In this paper, a new compact tunable microstrip-line fed slot antenna is proposed for interweave cognitive radio (CR) front end systems. The proposed antenna utilized four varactor diodes to control the antenna resonant frequency. The resonant frequency of the antenna can be electronically tuned by changing the effective electrical length of the resonant slot, which is accomplished by employing the varactor diodes inside the slot. Moreover, the simple biasing of the varactor diodes has a small effect on the antenna performance. Simulation results show that the proposed antenna is capable of frequency switching over a tuning range of 0.93 GHz from 1.83 to 2.76 GHz with 40.5 % frequency tuning range. The proposed antenna has a miniaturized size of 25 × 30 × 0.762 mm3.","PeriodicalId":362288,"journal":{"name":"2016 Fourth International Japan-Egypt Conference on Electronics, Communications and Computers (JEC-ECC)","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132798704","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 : 2016-07-21DOI: 10.1109/JEC-ECC.2016.7518973
Yoshihiro Tanaka, Keitarou Oka, Takatsugu Ono, Koji Inoue
This paper analyzes accuracy of performance models generated by machine learning-based empirical modeling methodology. Although the accuracy strongly depends on the quality of learning procedure, it is not clear what kind of learning algorithms and training data set (or feature) should be used. This paper inclusively explores the learning space of processor performance modeling as a case study. We focus on static architectural parameters as training data set such as cache size and clock frequency. Experimental results show that a tree-based non-linear regression modeling is superior to a stepwise linear regression modeling. Another observation is that clock frequency is the most important feature to improve prediction accuracy.
{"title":"Accuracy analysis of machine learning-based performance modeling for microprocessors","authors":"Yoshihiro Tanaka, Keitarou Oka, Takatsugu Ono, Koji Inoue","doi":"10.1109/JEC-ECC.2016.7518973","DOIUrl":"https://doi.org/10.1109/JEC-ECC.2016.7518973","url":null,"abstract":"This paper analyzes accuracy of performance models generated by machine learning-based empirical modeling methodology. Although the accuracy strongly depends on the quality of learning procedure, it is not clear what kind of learning algorithms and training data set (or feature) should be used. This paper inclusively explores the learning space of processor performance modeling as a case study. We focus on static architectural parameters as training data set such as cache size and clock frequency. Experimental results show that a tree-based non-linear regression modeling is superior to a stepwise linear regression modeling. Another observation is that clock frequency is the most important feature to improve prediction accuracy.","PeriodicalId":362288,"journal":{"name":"2016 Fourth International Japan-Egypt Conference on Electronics, Communications and Computers (JEC-ECC)","volume":"536 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123456804","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 : 2016-07-21DOI: 10.1109/JEC-ECC.2016.7518972
S. Mostafa, S. Kusakabe, H. Amano
Fairness measure is used in designing Operating System (OS) schedulers to determine whether users or applications are receiving a fair share of system resources. PS (proportional share) schedulers are the dominant schedulers in Virtual Machine (VM) environment. A PS scheduler assigns a weight to every VM to allocate CPU cycles, allocating these cycles to VM is proportional to that weight. Current VM scheduling algorithms don't aware about the attributes (e.g. weights and number of threads) of the running processes in VMs. We illustrate this issue through experimental evaluations of the current scheduling thus revealing its weakness. A modification of current scheduler is proposed in this work to enable users to specify weights to VMs. Therefore, user gets CPU usage proportion to the assigned weight, the higher weight the more CPU usage and vice versa. In addition, a pricing calculator is considered to calculate the fee that the user should pay according to his desired CPU usage. Derived results show that our modification achieves accurate proportional fairness for a diverse set of workloads.
{"title":"Fairness scheduler for multithreaded programs in Virtual Machine environment","authors":"S. Mostafa, S. Kusakabe, H. Amano","doi":"10.1109/JEC-ECC.2016.7518972","DOIUrl":"https://doi.org/10.1109/JEC-ECC.2016.7518972","url":null,"abstract":"Fairness measure is used in designing Operating System (OS) schedulers to determine whether users or applications are receiving a fair share of system resources. PS (proportional share) schedulers are the dominant schedulers in Virtual Machine (VM) environment. A PS scheduler assigns a weight to every VM to allocate CPU cycles, allocating these cycles to VM is proportional to that weight. Current VM scheduling algorithms don't aware about the attributes (e.g. weights and number of threads) of the running processes in VMs. We illustrate this issue through experimental evaluations of the current scheduling thus revealing its weakness. A modification of current scheduler is proposed in this work to enable users to specify weights to VMs. Therefore, user gets CPU usage proportion to the assigned weight, the higher weight the more CPU usage and vice versa. In addition, a pricing calculator is considered to calculate the fee that the user should pay according to his desired CPU usage. Derived results show that our modification achieves accurate proportional fairness for a diverse set of workloads.","PeriodicalId":362288,"journal":{"name":"2016 Fourth International Japan-Egypt Conference on Electronics, Communications and Computers (JEC-ECC)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-07-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134316524","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 : 2016-05-01DOI: 10.1109/JEC-ECC.2016.7518965
A. A. Hamdi, M. Sayed, M. Fouad, M. Hadhoud
This paper introduces a fully automated approach for defect detection in patterned fabrics. First, the fabric pattern period is determined by calculating the image mean vectors in both horizontal and vertical directions. Second, Gray Level Co-occurrence matrices are calculated to both the reference defect-free image and defected image after dividing them to blocks that have the same dimension as the fabric pattern. Third, Euclidean distances are calculated between each gray level co-occurrence matrix and a reference one for both defect-free and defected images. Forth, the resultant Euclidean distances are compared to pre-calculated thresholds to identify the defected blocks. The experimental results show that the proposed algorithm can achieve high detection accuracy rate besides its simplicity.
{"title":"Fully automated approach for patterned fabric defect detection","authors":"A. A. Hamdi, M. Sayed, M. Fouad, M. Hadhoud","doi":"10.1109/JEC-ECC.2016.7518965","DOIUrl":"https://doi.org/10.1109/JEC-ECC.2016.7518965","url":null,"abstract":"This paper introduces a fully automated approach for defect detection in patterned fabrics. First, the fabric pattern period is determined by calculating the image mean vectors in both horizontal and vertical directions. Second, Gray Level Co-occurrence matrices are calculated to both the reference defect-free image and defected image after dividing them to blocks that have the same dimension as the fabric pattern. Third, Euclidean distances are calculated between each gray level co-occurrence matrix and a reference one for both defect-free and defected images. Forth, the resultant Euclidean distances are compared to pre-calculated thresholds to identify the defected blocks. The experimental results show that the proposed algorithm can achieve high detection accuracy rate besides its simplicity.","PeriodicalId":362288,"journal":{"name":"2016 Fourth International Japan-Egypt Conference on Electronics, Communications and Computers (JEC-ECC)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129518432","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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