Pub Date : 2020-12-01DOI: 10.1109/ICRAIE51050.2020.9358352
Mahendra Kumar Gupta, Nutan Kumar Tomar, Dipa Sharma, Juhi Jaiswal
Proportional derivative (PD) observers are designed for linear descriptor systems with unknown inputs. Observer existence conditions are provided in the form of rank conditions directly on system matrices. Observer matrices are constructed by pole placement method and Linear Matrix Inequality (LMI) approach. The application of the work is demonstrated on a mathematical model of an infinite bus system. The efficiency of the proposed method is shown by simulation results.
{"title":"PD Observer Design for Descriptor Systems with Unknown Inputs: Application to Infinite Bus System","authors":"Mahendra Kumar Gupta, Nutan Kumar Tomar, Dipa Sharma, Juhi Jaiswal","doi":"10.1109/ICRAIE51050.2020.9358352","DOIUrl":"https://doi.org/10.1109/ICRAIE51050.2020.9358352","url":null,"abstract":"Proportional derivative (PD) observers are designed for linear descriptor systems with unknown inputs. Observer existence conditions are provided in the form of rank conditions directly on system matrices. Observer matrices are constructed by pole placement method and Linear Matrix Inequality (LMI) approach. The application of the work is demonstrated on a mathematical model of an infinite bus system. The efficiency of the proposed method is shown by simulation results.","PeriodicalId":149717,"journal":{"name":"2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121283501","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 : 2020-12-01DOI: 10.1109/ICRAIE51050.2020.9358306
Debadrata Sarkar, Sayantan Pal, S. Roy, Amit Kumar, Aman Arora
The article presents a technique to estimate the force transmitted in pneumatic artificial muscle based assistive devices by sensorizing the actuator. For this purpose, the development of a conductive liquid metal based elastomeric strain sensor has been discussed with the required characterization of its performance. A comparative analysis is shown between the modes of attachment of the developed sensor on the actuator so as to obtain a proper range of response from the sensor. A two-step algorithm has been implemented to estimate the force transmitted in series from an actuator used to assist the human knee and ankle during walking. The estimation results are validated against the readings from an actual inline loadcell, showing good agreement with one another.
{"title":"Estimation of Transmission Force in Assistive Devices using Conductive Liquid Metal based Sensorized Pneumatic Artificial Muscle","authors":"Debadrata Sarkar, Sayantan Pal, S. Roy, Amit Kumar, Aman Arora","doi":"10.1109/ICRAIE51050.2020.9358306","DOIUrl":"https://doi.org/10.1109/ICRAIE51050.2020.9358306","url":null,"abstract":"The article presents a technique to estimate the force transmitted in pneumatic artificial muscle based assistive devices by sensorizing the actuator. For this purpose, the development of a conductive liquid metal based elastomeric strain sensor has been discussed with the required characterization of its performance. A comparative analysis is shown between the modes of attachment of the developed sensor on the actuator so as to obtain a proper range of response from the sensor. A two-step algorithm has been implemented to estimate the force transmitted in series from an actuator used to assist the human knee and ankle during walking. The estimation results are validated against the readings from an actual inline loadcell, showing good agreement with one another.","PeriodicalId":149717,"journal":{"name":"2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125205185","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 : 2020-12-01DOI: 10.1109/ICRAIE51050.2020.9358353
Vaishali Shirsath, R. Agrawal
In most of the review article wind power based on mechanical design parameters or based on the reliability analysis of the wind farm is presented. In this review paper we presented analysis of wind power based on mechanical design parameters, reliability parameter and consideration electrical power in addition to Wind Canyon Model. There is a need to optimize design parameters of wind farm such as turbine size, weight, gear ratio parameters to achieve quality power as output which can sustain and maintain its availability with maximum efficiency. This article provides critical review of previous researcher. Paper also presents a detailed direction for wind analysis considering most and important constraint. Mathematical modeling is an important task for the modeling. This article discusses Mathematical modeling for wind data. Review of many research papers on reliability analysis specifically based on wind turbines between the 1999 to 2020 are presented. Since the last years many researchers focused on data collected on the reliability in wind turbines and published findings in different journals and articles are also noted. The issues in wind research is also addressed in this article. The review shows mechanical design analysis, reliability analysis and power optimization techniques. The critical findings provided here is helpful for other researcher. A combined objective function or cost function needs to develop subjected to constraints to achieve maximum profit through this business. A research work is required to improve the design variable in wind generator in addition to Wind power aspects such as power efficiency in addition to reliability.
{"title":"Optimization Through Wind Modeling by Means of Mechanical Design to Enhance Wind Power Generation and System Reliability","authors":"Vaishali Shirsath, R. Agrawal","doi":"10.1109/ICRAIE51050.2020.9358353","DOIUrl":"https://doi.org/10.1109/ICRAIE51050.2020.9358353","url":null,"abstract":"In most of the review article wind power based on mechanical design parameters or based on the reliability analysis of the wind farm is presented. In this review paper we presented analysis of wind power based on mechanical design parameters, reliability parameter and consideration electrical power in addition to Wind Canyon Model. There is a need to optimize design parameters of wind farm such as turbine size, weight, gear ratio parameters to achieve quality power as output which can sustain and maintain its availability with maximum efficiency. This article provides critical review of previous researcher. Paper also presents a detailed direction for wind analysis considering most and important constraint. Mathematical modeling is an important task for the modeling. This article discusses Mathematical modeling for wind data. Review of many research papers on reliability analysis specifically based on wind turbines between the 1999 to 2020 are presented. Since the last years many researchers focused on data collected on the reliability in wind turbines and published findings in different journals and articles are also noted. The issues in wind research is also addressed in this article. The review shows mechanical design analysis, reliability analysis and power optimization techniques. The critical findings provided here is helpful for other researcher. A combined objective function or cost function needs to develop subjected to constraints to achieve maximum profit through this business. A research work is required to improve the design variable in wind generator in addition to Wind power aspects such as power efficiency in addition to reliability.","PeriodicalId":149717,"journal":{"name":"2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128486427","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 : 2020-12-01DOI: 10.1109/ICRAIE51050.2020.9358385
B. Karthika, V. R. Jisha
Two wheeled self balancing robots have dynamic behaviour and are unstable in nature. Due to this, stabilizing of these robots has become a field of interest to many researchers. Around the equilibrium point of two wheeled self balancing mobile robot, the pitch angles are very small. Hence the balancing is achieved commonly by using linear control methods such as LQR(Linear Quadratic Regulator) control, PID(Proportional Integral Derivative) control etc. But the robots with large pitch angles tends to be in a region of high nonlinear behavior. Hence the linear control techniques fails in maintaining the balance of the robot. To remedy this problem and for improving the performances of the robot, an SDRE(State Dependent Riccati Equation) controller is designed along with SDC (State Dependent Coefficient) Matrix. Simulations are done to check the stability using SDRE controllers. A comparison is done using SDRE, PID and LQR controllers for the system with nonlinear dynamics. Also a comparison is done using PID and LQR controllers for the system with linear dynamics. From the simulations it is clear that SDRE controller shows excellent balancing for the two wheeled self balancing robot when compared to PID and LQR controllers.
{"title":"Nonlinear Optimal Control of a Two Wheeled Self Balancing Robot","authors":"B. Karthika, V. R. Jisha","doi":"10.1109/ICRAIE51050.2020.9358385","DOIUrl":"https://doi.org/10.1109/ICRAIE51050.2020.9358385","url":null,"abstract":"Two wheeled self balancing robots have dynamic behaviour and are unstable in nature. Due to this, stabilizing of these robots has become a field of interest to many researchers. Around the equilibrium point of two wheeled self balancing mobile robot, the pitch angles are very small. Hence the balancing is achieved commonly by using linear control methods such as LQR(Linear Quadratic Regulator) control, PID(Proportional Integral Derivative) control etc. But the robots with large pitch angles tends to be in a region of high nonlinear behavior. Hence the linear control techniques fails in maintaining the balance of the robot. To remedy this problem and for improving the performances of the robot, an SDRE(State Dependent Riccati Equation) controller is designed along with SDC (State Dependent Coefficient) Matrix. Simulations are done to check the stability using SDRE controllers. A comparison is done using SDRE, PID and LQR controllers for the system with nonlinear dynamics. Also a comparison is done using PID and LQR controllers for the system with linear dynamics. From the simulations it is clear that SDRE controller shows excellent balancing for the two wheeled self balancing robot when compared to PID and LQR controllers.","PeriodicalId":149717,"journal":{"name":"2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129517618","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 : 2020-12-01DOI: 10.1109/ICRAIE51050.2020.9358345
Aradhana Khillo, S. S. Patnaik
This paper provides the PSO based control scheme for regulation of active power and reactive power flow across the HVDC-VSC.VSC-HVDC system provides freedom of individual and independent control of active and reactive power in synchronous reference frame. PSO is based on the principle of “survival of the fittest”, originating from the idea of describing the mechanism of natural selection of the best food location. PSO provides the scope of self-tuning of the PI controller i.e with the change in system operating condition, the controller adjusts itself or tunes itself, thereby regulating the active power and reactive power. Also, PSO depend on the value of the objective function thereby making the computation less tedious and easy for implementation. The system is subjected to AC faults, and the response of the system is validated using MATLAB/SIMULINK platform.
{"title":"Performance Analysis of 6-Pulse HVDC-VSC using Particle Swarm Optimization(PSO) Based controller in d-q Reference Frame Under Transient AC Fault Conditions","authors":"Aradhana Khillo, S. S. Patnaik","doi":"10.1109/ICRAIE51050.2020.9358345","DOIUrl":"https://doi.org/10.1109/ICRAIE51050.2020.9358345","url":null,"abstract":"This paper provides the PSO based control scheme for regulation of active power and reactive power flow across the HVDC-VSC.VSC-HVDC system provides freedom of individual and independent control of active and reactive power in synchronous reference frame. PSO is based on the principle of “survival of the fittest”, originating from the idea of describing the mechanism of natural selection of the best food location. PSO provides the scope of self-tuning of the PI controller i.e with the change in system operating condition, the controller adjusts itself or tunes itself, thereby regulating the active power and reactive power. Also, PSO depend on the value of the objective function thereby making the computation less tedious and easy for implementation. The system is subjected to AC faults, and the response of the system is validated using MATLAB/SIMULINK platform.","PeriodicalId":149717,"journal":{"name":"2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129762777","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 : 2020-12-01DOI: 10.1109/ICRAIE51050.2020.9358379
Apar Garg, Rohit Kumar Kaliyar
In the current era of computing, the use of social networking sites like Twitter and Facebook, is growing significantly over time. People from different cultures and backgrounds share vast volumes of textual comments that show their viewpoints on several aspects of life and make them available to all for commenting. Monitoring real social media activities has now become a prime concern for politicians in understanding their social image. In this paper, we are going to analyse the tweets of various social media platforms regarding two prominent political leaders and classify them as positive, negative or neutral using Machine Learning and Deep Learning methods. We have proposed a Deep Learning approach for a better solution. Our proposed model has provided state-of-the-art results using Deep Learning models.
{"title":"PSent20: An Effective Political Sentiment Analysis with Deep Learning Using Real-Time Social Media Tweets","authors":"Apar Garg, Rohit Kumar Kaliyar","doi":"10.1109/ICRAIE51050.2020.9358379","DOIUrl":"https://doi.org/10.1109/ICRAIE51050.2020.9358379","url":null,"abstract":"In the current era of computing, the use of social networking sites like Twitter and Facebook, is growing significantly over time. People from different cultures and backgrounds share vast volumes of textual comments that show their viewpoints on several aspects of life and make them available to all for commenting. Monitoring real social media activities has now become a prime concern for politicians in understanding their social image. In this paper, we are going to analyse the tweets of various social media platforms regarding two prominent political leaders and classify them as positive, negative or neutral using Machine Learning and Deep Learning methods. We have proposed a Deep Learning approach for a better solution. Our proposed model has provided state-of-the-art results using Deep Learning models.","PeriodicalId":149717,"journal":{"name":"2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130300650","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 : 2020-12-01DOI: 10.1109/ICRAIE51050.2020.9358275
Naved Kalal, Sameer Dhanawale, R. Ghadge, Kulwantsinh Nimbalkar, Madhuri K. Gawali
Learning is a key to perform ideas adequately. Machine Learning empowers IT organizations to identify the patterns on the basis of currently available algorithms and data frames to cultivate acceptable solution concepts. Online business market and customer retention is a relation like the two sides of a coin. It is a nonlinear relationship. Prediction of Business growth is a very sensitive issue of E-Commerce market with its future existence. Online venders of business market manage their inventories on virtual prediction bases for full filling the basic need of demand-supply chain of customers. Authorizing traditional ways and analysis methods are not ensuring the rate of reliability of the sales prediction. To produce more precise predictions and analysis, we use ML algorithm. In this paper, we utilized the selling data set of an E-commerce company and segregated it, in different quarters then calculating the sale income per quarter. After that we divided the dataset in the proportion of 70% and 30% for Training data set and Testing data set. By applying machine learning algorithm, we will be predicting income of next quarters as well as analysis the maximally sold commodities with their frequencies of purchase per quarter. Then provide analysis results and prediction of customer's purchase patterns to the business organization to make a strategy to take a competitive advantage by sustaining and accumulating for their goods management and planning for inventories.
{"title":"Study for the Prediction of E-Commerce Business Market Growth using Machine Learning Algorithm","authors":"Naved Kalal, Sameer Dhanawale, R. Ghadge, Kulwantsinh Nimbalkar, Madhuri K. Gawali","doi":"10.1109/ICRAIE51050.2020.9358275","DOIUrl":"https://doi.org/10.1109/ICRAIE51050.2020.9358275","url":null,"abstract":"Learning is a key to perform ideas adequately. Machine Learning empowers IT organizations to identify the patterns on the basis of currently available algorithms and data frames to cultivate acceptable solution concepts. Online business market and customer retention is a relation like the two sides of a coin. It is a nonlinear relationship. Prediction of Business growth is a very sensitive issue of E-Commerce market with its future existence. Online venders of business market manage their inventories on virtual prediction bases for full filling the basic need of demand-supply chain of customers. Authorizing traditional ways and analysis methods are not ensuring the rate of reliability of the sales prediction. To produce more precise predictions and analysis, we use ML algorithm. In this paper, we utilized the selling data set of an E-commerce company and segregated it, in different quarters then calculating the sale income per quarter. After that we divided the dataset in the proportion of 70% and 30% for Training data set and Testing data set. By applying machine learning algorithm, we will be predicting income of next quarters as well as analysis the maximally sold commodities with their frequencies of purchase per quarter. Then provide analysis results and prediction of customer's purchase patterns to the business organization to make a strategy to take a competitive advantage by sustaining and accumulating for their goods management and planning for inventories.","PeriodicalId":149717,"journal":{"name":"2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131160113","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 : 2020-12-01DOI: 10.1109/ICRAIE51050.2020.9358300
Smriti Jain, R. Pachar, L. Gidwani
Unit commitment is becoming a complex problem with the increasing constraints due to the restructuring of power system and the escalation in inclusion of various types of Distributed Generation sources. These sources offer a significantly lower generation compared to the conventional sources. Also they pose synchronising problems with the grid since the electricity cannot be transmitted over long distances and thus they provide the localized consumption of energy. In this paper, unit commitment is performed with optimal spinning reserve allocation and the assessment of reliability in terms of loss of load, in the presence of solar integration into the power system. The ‘Loss Of Load Probability’ (LOLP) index is utilized for determining the level of reliability of the obtained results. The Spinning Reserve (SR) considered in the UC calculations, is a constant value and it is not varied with respect to the changes in solar generation. Here, the spinning reserve optimality is determined with respect to the changes in power injection due to the solar energy integration into the power system. Dynamic programming technique is applied on two systems (four generator and ten generator systems) and the results are compared with those obtained without the consideration of LOLP, SR optimality and solar energy sources.
{"title":"Reliability Constrained Day Ahead Unit Commitment with Optimal Spinning Reserve Allocation for Solar Integrated Power System","authors":"Smriti Jain, R. Pachar, L. Gidwani","doi":"10.1109/ICRAIE51050.2020.9358300","DOIUrl":"https://doi.org/10.1109/ICRAIE51050.2020.9358300","url":null,"abstract":"Unit commitment is becoming a complex problem with the increasing constraints due to the restructuring of power system and the escalation in inclusion of various types of Distributed Generation sources. These sources offer a significantly lower generation compared to the conventional sources. Also they pose synchronising problems with the grid since the electricity cannot be transmitted over long distances and thus they provide the localized consumption of energy. In this paper, unit commitment is performed with optimal spinning reserve allocation and the assessment of reliability in terms of loss of load, in the presence of solar integration into the power system. The ‘Loss Of Load Probability’ (LOLP) index is utilized for determining the level of reliability of the obtained results. The Spinning Reserve (SR) considered in the UC calculations, is a constant value and it is not varied with respect to the changes in solar generation. Here, the spinning reserve optimality is determined with respect to the changes in power injection due to the solar energy integration into the power system. Dynamic programming technique is applied on two systems (four generator and ten generator systems) and the results are compared with those obtained without the consideration of LOLP, SR optimality and solar energy sources.","PeriodicalId":149717,"journal":{"name":"2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132655620","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 : 2020-12-01DOI: 10.1109/ICRAIE51050.2020.9358294
P. Nandankar, P. Bedekar, P. V. Dhawas
In this research paper, load adaptive high efficiency DC-DC converter with optimized switching control is suggested. The converter is controlled over a wide load range by auto-tuning the switching frequency. The desired switching frequency is selected depend upon load current value. The new algorithm is presented to adapt the loading condition while maintaining the constant output voltage. This algorithm is implemented in a simulation environment where converter continuously maintains the optimal switching frequency under varying converter parameters and operating conditions. This Adaptive frequency Optimization (AFO) proposed controller performance is simulated and proposed algorithm is verified successfully. The efficiency curves are also plotted for different values of load current which provides validation of proposed adaptive frequency optimization algorithm.
{"title":"Efficient DC-DC Converter Using Variable Switching Frequency Digital Controller","authors":"P. Nandankar, P. Bedekar, P. V. Dhawas","doi":"10.1109/ICRAIE51050.2020.9358294","DOIUrl":"https://doi.org/10.1109/ICRAIE51050.2020.9358294","url":null,"abstract":"In this research paper, load adaptive high efficiency DC-DC converter with optimized switching control is suggested. The converter is controlled over a wide load range by auto-tuning the switching frequency. The desired switching frequency is selected depend upon load current value. The new algorithm is presented to adapt the loading condition while maintaining the constant output voltage. This algorithm is implemented in a simulation environment where converter continuously maintains the optimal switching frequency under varying converter parameters and operating conditions. This Adaptive frequency Optimization (AFO) proposed controller performance is simulated and proposed algorithm is verified successfully. The efficiency curves are also plotted for different values of load current which provides validation of proposed adaptive frequency optimization algorithm.","PeriodicalId":149717,"journal":{"name":"2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122926931","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 : 2020-12-01DOI: 10.1109/ICRAIE51050.2020.9358387
Pushpa Koranga, Soma Kumawat
Due to the environmental factor like unbalanced air light, darkness, contrast, saturation and attenuation causes hazy image. Many techniques are used to produce good quality image that retain color, illumination and better edges which suffer from weak edges and halo artifacts. In this paper we will be discussing previously proposed method which is adopted to remove haze from image. Several methods have been adopted to remove haze such as image dehazing is classified into two types such as single image dehazing and multi image dehazing. Different techniques of Image dehazing have been discussed in this review and also their advantage and drawback.
{"title":"A Review on Comparison of Different Techniques of Image Dehazing","authors":"Pushpa Koranga, Soma Kumawat","doi":"10.1109/ICRAIE51050.2020.9358387","DOIUrl":"https://doi.org/10.1109/ICRAIE51050.2020.9358387","url":null,"abstract":"Due to the environmental factor like unbalanced air light, darkness, contrast, saturation and attenuation causes hazy image. Many techniques are used to produce good quality image that retain color, illumination and better edges which suffer from weak edges and halo artifacts. In this paper we will be discussing previously proposed method which is adopted to remove haze from image. Several methods have been adopted to remove haze such as image dehazing is classified into two types such as single image dehazing and multi image dehazing. Different techniques of Image dehazing have been discussed in this review and also their advantage and drawback.","PeriodicalId":149717,"journal":{"name":"2020 5th IEEE International Conference on Recent Advances and Innovations in Engineering (ICRAIE)","volume":"221 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123041144","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：