Pub Date : 2018-12-01DOI: 10.1109/ICACAT.2018.8933689
B. N. Pandey, A. Shrivastava, A. Rana
The satellite image segmentation is a key area for current research and numerous work has been done for exploration of this area. The nature inspired optimization algorithms are very promising with image segmentation techniques to provide a platform for processing of satellite images. In this paper a literature review of different nature based optimization algorithms such as modified artificial bee colony (MABC) algorithm, ABC algorithm, particle swarm optimization (PSO), Darwinian PSO, genetic algorithm (GA), Wind driven optimization (WDO) and cuckoo search(CS) using different objective functions has been discussed to find the optimized multilevel thresholds. These nature influenced optimization methods and their performances are compared using different objective functions for optimal multilevel thresholding. The comparative study shows that the MABC algorithm and different variants of CS algorithm are very strong and accurate in results generating using image segmentation. Both methods search multilevel thresholds very efficiently and correctly, and in MABC an improved bee’s search solution are used and in CS the cuckoo search solution are used.
{"title":"A Literature Survey of Optimization Techniques for Satellite Image Segmentation","authors":"B. N. Pandey, A. Shrivastava, A. Rana","doi":"10.1109/ICACAT.2018.8933689","DOIUrl":"https://doi.org/10.1109/ICACAT.2018.8933689","url":null,"abstract":"The satellite image segmentation is a key area for current research and numerous work has been done for exploration of this area. The nature inspired optimization algorithms are very promising with image segmentation techniques to provide a platform for processing of satellite images. In this paper a literature review of different nature based optimization algorithms such as modified artificial bee colony (MABC) algorithm, ABC algorithm, particle swarm optimization (PSO), Darwinian PSO, genetic algorithm (GA), Wind driven optimization (WDO) and cuckoo search(CS) using different objective functions has been discussed to find the optimized multilevel thresholds. These nature influenced optimization methods and their performances are compared using different objective functions for optimal multilevel thresholding. The comparative study shows that the MABC algorithm and different variants of CS algorithm are very strong and accurate in results generating using image segmentation. Both methods search multilevel thresholds very efficiently and correctly, and in MABC an improved bee’s search solution are used and in CS the cuckoo search solution are used.","PeriodicalId":6575,"journal":{"name":"2018 International Conference on Advanced Computation and Telecommunication (ICACAT)","volume":"33 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85486681","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 : 2018-12-01DOI: 10.1109/ICACAT.2018.8933533
A. Jarndal, T. Petrovic
This paper reports linear- and switching-mode oscillators based on GaN power device that can be used efficiently for wireless power transfer (WPT) applications. The proposed oscillators are designed using a packaged GaN high electron mobility transistor (HEMT) from Transphorm Inc. In the first design a class-AB has been adopted and implemented to provide lower harmonics oscillator that can be used for electromagnetic interference (EMI) sensitive WPT applications. In the second part, higher efficiency class-E oscillator based on the same transistor has been designed and implemented to provide an optimal solution for higher power WPT applications. Both oscillators have been implemented and tested. The oscillators produce high output voltage up 40 V with lower total harmonic distortion of around 10% for class-AB and higher efficiency of around 90% for class-E oscillator.
{"title":"GaN-Based Oscillators for Wireless Power Transfer Applications","authors":"A. Jarndal, T. Petrovic","doi":"10.1109/ICACAT.2018.8933533","DOIUrl":"https://doi.org/10.1109/ICACAT.2018.8933533","url":null,"abstract":"This paper reports linear- and switching-mode oscillators based on GaN power device that can be used efficiently for wireless power transfer (WPT) applications. The proposed oscillators are designed using a packaged GaN high electron mobility transistor (HEMT) from Transphorm Inc. In the first design a class-AB has been adopted and implemented to provide lower harmonics oscillator that can be used for electromagnetic interference (EMI) sensitive WPT applications. In the second part, higher efficiency class-E oscillator based on the same transistor has been designed and implemented to provide an optimal solution for higher power WPT applications. Both oscillators have been implemented and tested. The oscillators produce high output voltage up 40 V with lower total harmonic distortion of around 10% for class-AB and higher efficiency of around 90% for class-E oscillator.","PeriodicalId":6575,"journal":{"name":"2018 International Conference on Advanced Computation and Telecommunication (ICACAT)","volume":"10 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81625014","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 : 2018-12-01DOI: 10.1109/ICACAT.2018.8933731
Kavita Kushwah, R. Narvey, A. Singhal
The purpose of this study was to determine the muscle activity of upper trapezius muscle of different head posture at standing and sitting positions by using surface electromyography (sEMG) signals. This tool may be a non-invasive technique that enables the analysis of muscle activity. Human’s head posture is significant part of human body and have a big role to analyze posture of human body. During this approach surface electrodes are employed to record surface electromyography (sEMG) signals of head posture at different angles. It is discovered that the muscle action of upper trapezius at both standing and sitting position is higher at 60 degree of head pose, whereas it’s lower just in case of zero degree that may be a neutral posture of head. It was also found that the muscle activity at standing position is higher than that of sitting position and in the result right trapezius muscle is more activate in standing position than the sitting position. It was also investigated that the muscle activity in standing is higher than that of sitting position. It is suggested that the muscle activity of head posture is lower in neutral position of head.
{"title":"Head Posture Analysis using sEMG Signal","authors":"Kavita Kushwah, R. Narvey, A. Singhal","doi":"10.1109/ICACAT.2018.8933731","DOIUrl":"https://doi.org/10.1109/ICACAT.2018.8933731","url":null,"abstract":"The purpose of this study was to determine the muscle activity of upper trapezius muscle of different head posture at standing and sitting positions by using surface electromyography (sEMG) signals. This tool may be a non-invasive technique that enables the analysis of muscle activity. Human’s head posture is significant part of human body and have a big role to analyze posture of human body. During this approach surface electrodes are employed to record surface electromyography (sEMG) signals of head posture at different angles. It is discovered that the muscle action of upper trapezius at both standing and sitting position is higher at 60 degree of head pose, whereas it’s lower just in case of zero degree that may be a neutral posture of head. It was also found that the muscle activity at standing position is higher than that of sitting position and in the result right trapezius muscle is more activate in standing position than the sitting position. It was also investigated that the muscle activity in standing is higher than that of sitting position. It is suggested that the muscle activity of head posture is lower in neutral position of head.","PeriodicalId":6575,"journal":{"name":"2018 International Conference on Advanced Computation and Telecommunication (ICACAT)","volume":"299 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79655307","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 : 2018-12-01DOI: 10.1109/ICACAT.2018.8933717
S. M. Patil, K. Bhoyar
With the advent of digital cameras and mobile phones, advances in telecommunication and internet, millions of images are uploaded on the internet without much information about the image. An efficient method is necessary for automatic image annotation and indexing for the vast collection of images. Concept detection is task of detecting concepts present in image. In this paper, concept detection is obtained by effectively fusing local feature descriptors and global features descriptors. First object extraction is carried out using edge and color, and the aspect ratio of each extracted object is calculated. The local features of all extracted objects and global features of the image are computed. The detected concept of the query image is displayed based on the local and global feature matching scores obtained using our algorithm. The proposed algorithm is evaluated on Wang’s Corel dataset consisting of 1000 images. Results demonstrate that the proposed approach outperforms the KNN and ANN methods with high accuracy.
{"title":"Local and Global Feature Fusion Based Visual Concept Detection in Images","authors":"S. M. Patil, K. Bhoyar","doi":"10.1109/ICACAT.2018.8933717","DOIUrl":"https://doi.org/10.1109/ICACAT.2018.8933717","url":null,"abstract":"With the advent of digital cameras and mobile phones, advances in telecommunication and internet, millions of images are uploaded on the internet without much information about the image. An efficient method is necessary for automatic image annotation and indexing for the vast collection of images. Concept detection is task of detecting concepts present in image. In this paper, concept detection is obtained by effectively fusing local feature descriptors and global features descriptors. First object extraction is carried out using edge and color, and the aspect ratio of each extracted object is calculated. The local features of all extracted objects and global features of the image are computed. The detected concept of the query image is displayed based on the local and global feature matching scores obtained using our algorithm. The proposed algorithm is evaluated on Wang’s Corel dataset consisting of 1000 images. Results demonstrate that the proposed approach outperforms the KNN and ANN methods with high accuracy.","PeriodicalId":6575,"journal":{"name":"2018 International Conference on Advanced Computation and Telecommunication (ICACAT)","volume":"32 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80782781","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 : 2018-12-01DOI: 10.1109/ICACAT.2018.8933699
D. Thosar, Manmohan Singh
In today’s world of newly coming technologies, an authentication play’s an efficient role to provide authenticity to every user’s vital information from variety of system attacks. So we need to provide strong authenticity to avoid from such an unsecured problems. Up till now most of the users prefer text passwords to provide authenticity to their account. In many cases there will be a risk of textual password by selecting an irrelevant or easily remembered password or the way of putting it in the insecure way are said to be “the unsecured way” in the authentication chain. Except choosing a strong character set, the user will select the easier password which is less complicated or short or the text as a password which is easier to kept in mind. So with new & advanced, emerging technologies and a large set of mobile application to be developed on regular basis. Due to this user can access their account anytime, anywhere on mobiles, Laptops etc. It’s a better thing through which we decrease the time consumption but automatically increases the chance of exposing the credentials to the shoulder surfing attacker’s. It can be happened directly or indirectly with naked eyes or indirectly by using some hidden recording devices to detect user’sconfidential data.
{"title":"A Review on Advanced Graphical Authentication to Resist Shoulder Surfing Attack","authors":"D. Thosar, Manmohan Singh","doi":"10.1109/ICACAT.2018.8933699","DOIUrl":"https://doi.org/10.1109/ICACAT.2018.8933699","url":null,"abstract":"In today’s world of newly coming technologies, an authentication play’s an efficient role to provide authenticity to every user’s vital information from variety of system attacks. So we need to provide strong authenticity to avoid from such an unsecured problems. Up till now most of the users prefer text passwords to provide authenticity to their account. In many cases there will be a risk of textual password by selecting an irrelevant or easily remembered password or the way of putting it in the insecure way are said to be “the unsecured way” in the authentication chain. Except choosing a strong character set, the user will select the easier password which is less complicated or short or the text as a password which is easier to kept in mind. So with new & advanced, emerging technologies and a large set of mobile application to be developed on regular basis. Due to this user can access their account anytime, anywhere on mobiles, Laptops etc. It’s a better thing through which we decrease the time consumption but automatically increases the chance of exposing the credentials to the shoulder surfing attacker’s. It can be happened directly or indirectly with naked eyes or indirectly by using some hidden recording devices to detect user’sconfidential data.","PeriodicalId":6575,"journal":{"name":"2018 International Conference on Advanced Computation and Telecommunication (ICACAT)","volume":"42 1","pages":"1-3"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77818389","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 : 2018-12-01DOI: 10.1109/ICACAT.2018.8933790
Ranjana S. Jadhav, P. Ghadekar
Emotion recognition or sentiment analysis is identified as an important research topic in computer vision community. The challenges include identification of face, recognition of accurate emotion, appropriate database and so on. We have proposed and implemented a general Convolutional Neural network (CNN) building framework for emotion recognition. The model is formalized by developing a coincident system which fulfills the tasks of face detection and emotion classification using our proposed CNN architecture. The model is validated using the FER-2013 dataset. In the proposed work, we discuss the applicability of the proposed CNN model. This model lays a valuable analysis of the effect of adjusting the network size, pooling, and dropout. For a given model, the final accuracy on the validation data is around 63%.
{"title":"Content Based Facial Emotion Recognition Model using Machine Learning Algorithm","authors":"Ranjana S. Jadhav, P. Ghadekar","doi":"10.1109/ICACAT.2018.8933790","DOIUrl":"https://doi.org/10.1109/ICACAT.2018.8933790","url":null,"abstract":"Emotion recognition or sentiment analysis is identified as an important research topic in computer vision community. The challenges include identification of face, recognition of accurate emotion, appropriate database and so on. We have proposed and implemented a general Convolutional Neural network (CNN) building framework for emotion recognition. The model is formalized by developing a coincident system which fulfills the tasks of face detection and emotion classification using our proposed CNN architecture. The model is validated using the FER-2013 dataset. In the proposed work, we discuss the applicability of the proposed CNN model. This model lays a valuable analysis of the effect of adjusting the network size, pooling, and dropout. For a given model, the final accuracy on the validation data is around 63%.","PeriodicalId":6575,"journal":{"name":"2018 International Conference on Advanced Computation and Telecommunication (ICACAT)","volume":"12 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82895058","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 : 2018-12-01DOI: 10.1109/ICACAT.2018.8933787
A. Shrivastava, R. Dubey
Email is necessary and essential for communication in today's life. Today internet users are increases, and email is necessary for communication over the internet. Spam mail is a major and big problem of researchers to analyze and reduce it. Spam emails are received in bulk amount and it contains trojans, viruses, malware and causes phishing attacks. Problems are arise when number of unwanted mails are come from unknown sites and how to classify the user that email are received which is spam email or ham. This paper used to classify that incoming emails are spam mail or ham by the use of different classification techniques to identify spam mail and remove it. Naive bayes classifier are apply in the concept of posterior probability and decision tree algorithms are apply namely Random Tree, REPTree, Random Forest,and J48 decision tree classifier. For the identification of spam mail, UCI spambase dataset is used. It is a benchmark dataset which contains 58 attributes and 4601 instances. Weka software is used for the analysis and implementation of results. In Weka tool, classification algorithms are used to find spam mail in the classification phase of weka software.These papers play a very important role to remove viruses, trojans, malware and websites including phishing attacks and fraudulent attempts in emails. Feature selection is applied on dataset for training set and cross validation. Cfs Subset evaluation method is used for best first method in feature selection. For the classification of spam mail, we use two tests are cross validation and training set under classifier option in Weka Tool. For training set, same data will be used for training and testing. And for cross validation, training data is segmented in a number of folds. And finally using training set, Random Tree gives the best result for the classification of spam mail.
{"title":"Classification of Spam Mail using different machine learning algorithms","authors":"A. Shrivastava, R. Dubey","doi":"10.1109/ICACAT.2018.8933787","DOIUrl":"https://doi.org/10.1109/ICACAT.2018.8933787","url":null,"abstract":"Email is necessary and essential for communication in today's life. Today internet users are increases, and email is necessary for communication over the internet. Spam mail is a major and big problem of researchers to analyze and reduce it. Spam emails are received in bulk amount and it contains trojans, viruses, malware and causes phishing attacks. Problems are arise when number of unwanted mails are come from unknown sites and how to classify the user that email are received which is spam email or ham. This paper used to classify that incoming emails are spam mail or ham by the use of different classification techniques to identify spam mail and remove it. Naive bayes classifier are apply in the concept of posterior probability and decision tree algorithms are apply namely Random Tree, REPTree, Random Forest,and J48 decision tree classifier. For the identification of spam mail, UCI spambase dataset is used. It is a benchmark dataset which contains 58 attributes and 4601 instances. Weka software is used for the analysis and implementation of results. In Weka tool, classification algorithms are used to find spam mail in the classification phase of weka software.These papers play a very important role to remove viruses, trojans, malware and websites including phishing attacks and fraudulent attempts in emails. Feature selection is applied on dataset for training set and cross validation. Cfs Subset evaluation method is used for best first method in feature selection. For the classification of spam mail, we use two tests are cross validation and training set under classifier option in Weka Tool. For training set, same data will be used for training and testing. And for cross validation, training data is segmented in a number of folds. And finally using training set, Random Tree gives the best result for the classification of spam mail.","PeriodicalId":6575,"journal":{"name":"2018 International Conference on Advanced Computation and Telecommunication (ICACAT)","volume":"4 1","pages":"1-10"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87851345","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 : 2018-12-01DOI: 10.1109/ICACAT.2018.8933597
H. K. Dwivedi, Shuvendu Nandi, Shweta Lahariya, Sangeeta Nakhate
The work in this paper centres around comparison amongst conventional and RHBD technique based combinational and sequential standard cells in 0.18μmCMOS technology using SCL PDK in Cadence Virtuoso. In space radioactive particles (proton, neutrons, $alpha$) and heavy ions makes the biggest threat to Integrated Circuits (IC). With continuously decreasing feature size and lowering of the supply voltage, causes Single Event Transients (SETs) which is becoming a major problem for both combinational and sequential digital circuits in the Deep Submicron technology (DSM). The proposed C- element based cells investigated are Inverter, NAND gate, Buffer and D-Flip Flop. Schematic and layout of these cells are developed using Cadence Virtuoso tool. Circuits which are designed with the RHBD approaches are more tolerant to Single Event Effects (SEE), have better noise immunity and less static power consumption. The reduction in the average power in proposed style is 94% and the delay reduction is 85% as compared to DCVSL methodology.
{"title":"Combinational and sequential standard cell design using Radiation Hardened By Design (RHBD) Technique","authors":"H. K. Dwivedi, Shuvendu Nandi, Shweta Lahariya, Sangeeta Nakhate","doi":"10.1109/ICACAT.2018.8933597","DOIUrl":"https://doi.org/10.1109/ICACAT.2018.8933597","url":null,"abstract":"The work in this paper centres around comparison amongst conventional and RHBD technique based combinational and sequential standard cells in 0.18μmCMOS technology using SCL PDK in Cadence Virtuoso. In space radioactive particles (proton, neutrons, $alpha$) and heavy ions makes the biggest threat to Integrated Circuits (IC). With continuously decreasing feature size and lowering of the supply voltage, causes Single Event Transients (SETs) which is becoming a major problem for both combinational and sequential digital circuits in the Deep Submicron technology (DSM). The proposed C- element based cells investigated are Inverter, NAND gate, Buffer and D-Flip Flop. Schematic and layout of these cells are developed using Cadence Virtuoso tool. Circuits which are designed with the RHBD approaches are more tolerant to Single Event Effects (SEE), have better noise immunity and less static power consumption. The reduction in the average power in proposed style is 94% and the delay reduction is 85% as compared to DCVSL methodology.","PeriodicalId":6575,"journal":{"name":"2018 International Conference on Advanced Computation and Telecommunication (ICACAT)","volume":"25 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87402480","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 : 2018-12-01DOI: 10.1109/ICACAT.2018.8933809
Jagrati Gupta, S. Agrawal
Pixels of the digital images has been corrupted by noises came out of faulty communication channel or nonlinear sensors. Such noise models can be either Salt & pepper noise (impulse noise) or Gaussian noise. Sometimes both of the noises corrupt the same image; such combination of two noise model is called as mixed noise. These noises can be removed by using image filtering algorithms. The most popular image filtering algorithm is median filters. Two models of median filters, that are simple median filter and switching median filter has been discussed in this paper. Fuzzy logic controller has been discussed in details so that its combination with median filters can be discussed for future work. Terminologies like fuzzy logic operator, membership functions and fuzzy rules have been discussed. Quality parameter PSNR (Peak Signal to Noise Ratio) has been studied to find the quality of image numerically.
{"title":"Study of Median Filters and Fuzzy Rules for Filtering of Images Corrupted With Mixed Noise","authors":"Jagrati Gupta, S. Agrawal","doi":"10.1109/ICACAT.2018.8933809","DOIUrl":"https://doi.org/10.1109/ICACAT.2018.8933809","url":null,"abstract":"Pixels of the digital images has been corrupted by noises came out of faulty communication channel or nonlinear sensors. Such noise models can be either Salt & pepper noise (impulse noise) or Gaussian noise. Sometimes both of the noises corrupt the same image; such combination of two noise model is called as mixed noise. These noises can be removed by using image filtering algorithms. The most popular image filtering algorithm is median filters. Two models of median filters, that are simple median filter and switching median filter has been discussed in this paper. Fuzzy logic controller has been discussed in details so that its combination with median filters can be discussed for future work. Terminologies like fuzzy logic operator, membership functions and fuzzy rules have been discussed. Quality parameter PSNR (Peak Signal to Noise Ratio) has been studied to find the quality of image numerically.","PeriodicalId":6575,"journal":{"name":"2018 International Conference on Advanced Computation and Telecommunication (ICACAT)","volume":"1 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77517470","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 : 2018-12-01DOI: 10.1109/ICACAT.2018.8933594
B. Solanki, M. Ingle
Images are degraded during image procurement in terms of several disturbances. As a result, poor illumination, low contrast value, background blurring etc. occur in images that hampers its quality. Using thresholding process, we attempt to improve eminence of image, enhance contrast value as well as separates foreground and background information. There exist several prevailing thresholding techniques such as bernsen, wolf, sauvola, otsu, niblack and bradley for numerous scripts. A threshold model is proposed in this paper for binarizing Modi character images efficiently. It uses various global and local thresholding techniques in order to achieve high contrast value, better illumination etc. Two performance parameters such as mean square error and peak signal to noise ratio is used to measure the effects of varied thresholding techniques. As a result, Otsu thresholding technique shows effective outcome for binarizing Modi vowels in more appropriate form.
{"title":"Performance Evaluation of Thresholding Techniques on Modi Script","authors":"B. Solanki, M. Ingle","doi":"10.1109/ICACAT.2018.8933594","DOIUrl":"https://doi.org/10.1109/ICACAT.2018.8933594","url":null,"abstract":"Images are degraded during image procurement in terms of several disturbances. As a result, poor illumination, low contrast value, background blurring etc. occur in images that hampers its quality. Using thresholding process, we attempt to improve eminence of image, enhance contrast value as well as separates foreground and background information. There exist several prevailing thresholding techniques such as bernsen, wolf, sauvola, otsu, niblack and bradley for numerous scripts. A threshold model is proposed in this paper for binarizing Modi character images efficiently. It uses various global and local thresholding techniques in order to achieve high contrast value, better illumination etc. Two performance parameters such as mean square error and peak signal to noise ratio is used to measure the effects of varied thresholding techniques. As a result, Otsu thresholding technique shows effective outcome for binarizing Modi vowels in more appropriate form.","PeriodicalId":6575,"journal":{"name":"2018 International Conference on Advanced Computation and Telecommunication (ICACAT)","volume":"44 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90502589","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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