Pub Date : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9277189
H. K. Joy, Manjunath R. Kounte, Ajin K Joy
The basic processing unit of HEVC is CTU. It can possess various size from 64×64 to 8×8 and it increasing coding efficiency as size is large. The computational complexity is an issue to be focused as HEVC has many pros to be considered as a best video compression technique. This paper focus on reducing the computational complexity of high-efficiency video coding (HEVC) in intra prediction by using combining depth decision and deep learning techniques. The proposed method provides a neural network for depth analysis of CTU followed by a deep learning network with multiple sizes of kernels for convolution and pervasive parameters that are trainable, from the database provided. A database provided here is constructed considering both the image frame from video and encoding abilities of CU. Database has the image frame data indicating the image value of CU and a vector of 16x1 depending on CU’s encoding details. It has a label to indicate, whether the CU is split or not. Initially image frame that is of huge size is assorted to various scales and split is created. Followed by modelling the partitions into a three level classification problem. To solve classification issue, a deep learning based CNN structure that possess various size kernels and parameters for convolution is developed, that should be analyzed and learned through a database that is established. The results show a dip in the encoding time of intra mode in HEVC for the given database
{"title":"Deep Learning Approach in Intra -Prediction of High Efficiency Video Coding","authors":"H. K. Joy, Manjunath R. Kounte, Ajin K Joy","doi":"10.1109/ICSTCEE49637.2020.9277189","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9277189","url":null,"abstract":"The basic processing unit of HEVC is CTU. It can possess various size from 64×64 to 8×8 and it increasing coding efficiency as size is large. The computational complexity is an issue to be focused as HEVC has many pros to be considered as a best video compression technique. This paper focus on reducing the computational complexity of high-efficiency video coding (HEVC) in intra prediction by using combining depth decision and deep learning techniques. The proposed method provides a neural network for depth analysis of CTU followed by a deep learning network with multiple sizes of kernels for convolution and pervasive parameters that are trainable, from the database provided. A database provided here is constructed considering both the image frame from video and encoding abilities of CU. Database has the image frame data indicating the image value of CU and a vector of 16x1 depending on CU’s encoding details. It has a label to indicate, whether the CU is split or not. Initially image frame that is of huge size is assorted to various scales and split is created. Followed by modelling the partitions into a three level classification problem. To solve classification issue, a deep learning based CNN structure that possess various size kernels and parameters for convolution is developed, that should be analyzed and learned through a database that is established. The results show a dip in the encoding time of intra mode in HEVC for the given database","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133537377","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 : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9276846
A. Khalyasmaa, S. Eroshenko, Duc Chung Tran, Snegirev Denis
This paper addresses the study of operational photovoltaic power plant forecasting based on the results of short-term forecasts, thus providing the multi-level hierarchical system of solar power plant generation planning. The study provides the comparison between naive persistence, autoregressive and autoregressive moving average models with the corresponding parameters tuning in order to identify the most effective way to implement intra-day forecasting option. The case study is based on real photovoltaic power plant operational data in order to verify the opportunity of the presented approach practical implementation.
{"title":"Photovoltaic power plant production operational forecast based on its short-term forecasting model","authors":"A. Khalyasmaa, S. Eroshenko, Duc Chung Tran, Snegirev Denis","doi":"10.1109/ICSTCEE49637.2020.9276846","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9276846","url":null,"abstract":"This paper addresses the study of operational photovoltaic power plant forecasting based on the results of short-term forecasts, thus providing the multi-level hierarchical system of solar power plant generation planning. The study provides the comparison between naive persistence, autoregressive and autoregressive moving average models with the corresponding parameters tuning in order to identify the most effective way to implement intra-day forecasting option. The case study is based on real photovoltaic power plant operational data in order to verify the opportunity of the presented approach practical implementation.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"325 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122740130","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 : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9276496
Sundeep. Siddula, T. Achyut, K. Vigneshwar, M.V. UDAY TEJA
The Electricity is contemplated as the back bone for the industrial revolution and in order to conclave the meeting of both industrial and household needs electricity needs to be at an larger transmission. For this paving of the electricity and also regulating the issues which are cascading on the power system something Flexible need to be adapted. Flexible Alternating Current Transmission Systems (FACTS) has been a promising aspect in terms of the power system performance analysis. In this paper a comprehensive analysis on the Unified Power Flow Controller (UPFC) which being one of the FACTS device is presented. Accordingly the UPFC for different cases is perceived using a Proportional Integral(PI) controller and an Fuzzy logic controller (FLC). The Fuzzy logic controller is introduced, developed by the MAMDANI method replacing PI controller on a transmission line under different power system operating conditions. MATLAB/SIMULINK was used in order to delineate the controller network. It was observed that the UPFC with the Fuzzy logic based control technique in lines of alleviating the power quality issues like voltage sags, swells, damping had an superior performance than that of UPFC with the PI controller. It could be concluded that the Fuzzy logic controller(FLC) for mitigating the issues of power quality.
{"title":"Improvement of Power Quality Using Fuzzy Based Unified Power Flow Controller","authors":"Sundeep. Siddula, T. Achyut, K. Vigneshwar, M.V. UDAY TEJA","doi":"10.1109/ICSTCEE49637.2020.9276496","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9276496","url":null,"abstract":"The Electricity is contemplated as the back bone for the industrial revolution and in order to conclave the meeting of both industrial and household needs electricity needs to be at an larger transmission. For this paving of the electricity and also regulating the issues which are cascading on the power system something Flexible need to be adapted. Flexible Alternating Current Transmission Systems (FACTS) has been a promising aspect in terms of the power system performance analysis. In this paper a comprehensive analysis on the Unified Power Flow Controller (UPFC) which being one of the FACTS device is presented. Accordingly the UPFC for different cases is perceived using a Proportional Integral(PI) controller and an Fuzzy logic controller (FLC). The Fuzzy logic controller is introduced, developed by the MAMDANI method replacing PI controller on a transmission line under different power system operating conditions. MATLAB/SIMULINK was used in order to delineate the controller network. It was observed that the UPFC with the Fuzzy logic based control technique in lines of alleviating the power quality issues like voltage sags, swells, damping had an superior performance than that of UPFC with the PI controller. It could be concluded that the Fuzzy logic controller(FLC) for mitigating the issues of power quality.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"85 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116923306","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 : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9277288
Mary swarna Latha Gade, S. Rooban
Reliability and low power consumption are important design metrics of any critical embedded systems. With the advancements of fabrication technology reaching to the nano levels and complexity of system is increasing, systems are more exposed to manufacturing defects which leads to faults in the system. This paper is presenting a method to design ALU which employs a run time recovery mechanism in order to detect both hardware and transient faults. The proposed method is a recomputing using duplication with comparison (RDWC) based on combination of time and hardware redundancy techniques. Simulation results indicate, RDWC incurs a decrease in LUT overhead of 124%, IO (input output) overhead by 129% and power overhead of 35% compared to the existing TMR technique.
{"title":"Run Time Fault Tolerant Mechanism for Transient and Hardware Faults in ALU for Highly Reliable Embedded Processor","authors":"Mary swarna Latha Gade, S. Rooban","doi":"10.1109/ICSTCEE49637.2020.9277288","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9277288","url":null,"abstract":"Reliability and low power consumption are important design metrics of any critical embedded systems. With the advancements of fabrication technology reaching to the nano levels and complexity of system is increasing, systems are more exposed to manufacturing defects which leads to faults in the system. This paper is presenting a method to design ALU which employs a run time recovery mechanism in order to detect both hardware and transient faults. The proposed method is a recomputing using duplication with comparison (RDWC) based on combination of time and hardware redundancy techniques. Simulation results indicate, RDWC incurs a decrease in LUT overhead of 124%, IO (input output) overhead by 129% and power overhead of 35% compared to the existing TMR technique.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129232261","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 : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9277113
S. Muthu, Vignesh Ravisekar, Abishek Anand Anandhan Sasimahadevi, T. Mohan, Aswin Baskaran, Vedanarayanan Sridheepa Rajagopalan, D. Ganesh, Sumathi Sokkanarayanan, Mithileysh Sathiyanarayanan
Telecommunication is the transmission of information over electromagnetic systems using technologies such as radio, wire, etc. Mobile phones are the most popular form of telecommunication. As a result, the usage of smartphones has drastically increased each year. And even during this current pandemic COVID-19, the usage of smartphones and internet has tremendously increased. Some significant applications include banking applications, education sectors (online classes), virtual meetings, e-commerce, travel, recreation etc. As the usage increases, there arises a frequent charge and discharge cycle. Enormous amount of energy is generated every day while carrying our daily activities by means of which, a significant amount of pressure is developed. Using this energy, an efficient model is proposed which uses piezoelectric and thermoelectric sensors to generate energy to suffice the daily needs of a common man. As aligning with the SDG goal number 7 - affordable and clean energy, the proposed idea is a step towards attaining a sustainable future.
{"title":"PowerVolt: Wireless Charging for Mobile Devices Using Renewable Power Generation System","authors":"S. Muthu, Vignesh Ravisekar, Abishek Anand Anandhan Sasimahadevi, T. Mohan, Aswin Baskaran, Vedanarayanan Sridheepa Rajagopalan, D. Ganesh, Sumathi Sokkanarayanan, Mithileysh Sathiyanarayanan","doi":"10.1109/ICSTCEE49637.2020.9277113","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9277113","url":null,"abstract":"Telecommunication is the transmission of information over electromagnetic systems using technologies such as radio, wire, etc. Mobile phones are the most popular form of telecommunication. As a result, the usage of smartphones has drastically increased each year. And even during this current pandemic COVID-19, the usage of smartphones and internet has tremendously increased. Some significant applications include banking applications, education sectors (online classes), virtual meetings, e-commerce, travel, recreation etc. As the usage increases, there arises a frequent charge and discharge cycle. Enormous amount of energy is generated every day while carrying our daily activities by means of which, a significant amount of pressure is developed. Using this energy, an efficient model is proposed which uses piezoelectric and thermoelectric sensors to generate energy to suffice the daily needs of a common man. As aligning with the SDG goal number 7 - affordable and clean energy, the proposed idea is a step towards attaining a sustainable future.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115285155","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 : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9276792
N. L., B. Cv, B. Singh, Vinod S. Chippalakatti
Forward Converter is highly preferred for designing Power Supply Units in space applications, because of its simple structure and provides perfect isolation between input and output .The design of precision converters should take care of variation of the power supply voltage. In achieving Closed Loop implementation of DC-DC converter, Coupled Inductor is considered very effective as Post-regulator for Forward Converter. The proposed Inductor is designed on the basis of transformer and filter Inductor turns. Inductor designed in this manner provides faster response, better coupling and reduces leakage. This coupled Inductor design can be effectively utilized to other isolated topologies. The proposed topology can be used for space applications and it has been demonstrated experimentally delivering three outputs of the range 5V/4A,+15V/0.677A and -15V/0.677A from an input range of 18-50V, also with an efficiency of greater than 78% at full load.
{"title":"Design and Implementation of Triple Output Forward DC-DC Converter with Coupled Inductor as Post-regulator for Space Application","authors":"N. L., B. Cv, B. Singh, Vinod S. Chippalakatti","doi":"10.1109/ICSTCEE49637.2020.9276792","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9276792","url":null,"abstract":"Forward Converter is highly preferred for designing Power Supply Units in space applications, because of its simple structure and provides perfect isolation between input and output .The design of precision converters should take care of variation of the power supply voltage. In achieving Closed Loop implementation of DC-DC converter, Coupled Inductor is considered very effective as Post-regulator for Forward Converter. The proposed Inductor is designed on the basis of transformer and filter Inductor turns. Inductor designed in this manner provides faster response, better coupling and reduces leakage. This coupled Inductor design can be effectively utilized to other isolated topologies. The proposed topology can be used for space applications and it has been demonstrated experimentally delivering three outputs of the range 5V/4A,+15V/0.677A and -15V/0.677A from an input range of 18-50V, also with an efficiency of greater than 78% at full load.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128485863","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 : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9277286
Sandali Raizada, Shuchi Mala, A. Shankar
Vector Borne Disease is a form of illness which is caused by parasites, viruses and bacteria. The infection is transferred through blood-feeding arthropods such as mosquitoes, fleas ticks etc. Every year from diseases such as yellow fever, Malaria more than 700,000 deaths occur. These diseases are most common in tropical and subtropical areas and affect the underprivileged populations. Deep learning an essential part of Artificial Intelligence provides an uncanny power to systems to construct a complex network using layers of perceptrons which mimic the human neurons. This network Combined with algorithms of Machine Learning may serve as one of the most powerful tool in healthcare to classify and analyze huge amount of medical data and predict future trends through Supervised Learning. The paper we focused on effective prediction of the vector borne disease outbreak (Multiclass Classification) of three diseases (Chikungunya, Malaria, Dengue) across the Indian-subcontinent. We have examined and refined our model over data collected across India in 2013-2017. We have put forward a Convolutional Neural Network outbreak risk prediction algorithm using contrasting data. To our finest understanding, none of the previous works have centered on contrasting data in area of analysis of medical data. The prediction accuracy of our suggested CNN algorithm is 88%.
{"title":"Vector Borne Disease Outbreak Prediction by Machine Learning","authors":"Sandali Raizada, Shuchi Mala, A. Shankar","doi":"10.1109/ICSTCEE49637.2020.9277286","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9277286","url":null,"abstract":"Vector Borne Disease is a form of illness which is caused by parasites, viruses and bacteria. The infection is transferred through blood-feeding arthropods such as mosquitoes, fleas ticks etc. Every year from diseases such as yellow fever, Malaria more than 700,000 deaths occur. These diseases are most common in tropical and subtropical areas and affect the underprivileged populations. Deep learning an essential part of Artificial Intelligence provides an uncanny power to systems to construct a complex network using layers of perceptrons which mimic the human neurons. This network Combined with algorithms of Machine Learning may serve as one of the most powerful tool in healthcare to classify and analyze huge amount of medical data and predict future trends through Supervised Learning. The paper we focused on effective prediction of the vector borne disease outbreak (Multiclass Classification) of three diseases (Chikungunya, Malaria, Dengue) across the Indian-subcontinent. We have examined and refined our model over data collected across India in 2013-2017. We have put forward a Convolutional Neural Network outbreak risk prediction algorithm using contrasting data. To our finest understanding, none of the previous works have centered on contrasting data in area of analysis of medical data. The prediction accuracy of our suggested CNN algorithm is 88%.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"228 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132653125","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 : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9277093
A. Harsha, S. Pranupa, B. K. Kiran Kumar, S. Nagaraja Rao, M. Indira
Induction Motors (IM) are work horse of power industries. Controlling of IM is crucial task in most of the applications. This paper presents implementation of a Variable Frequency Drive (VFD) controller for a three phase induction motor driven by single phase supply on an Arduino platform. The hardware setup involves a rectifier-inverter combination along with a DC link. The present work concentrates on programming the timers of ATMEGA 2560 microcontroller to obtain the required switching pulses. The simulation results of the developed switching control technique with due validation from a hardware setup are presented.
{"title":"Arduino based V/f Drive for a Three Phase Induction Motor using Single Phase Supply","authors":"A. Harsha, S. Pranupa, B. K. Kiran Kumar, S. Nagaraja Rao, M. Indira","doi":"10.1109/ICSTCEE49637.2020.9277093","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9277093","url":null,"abstract":"Induction Motors (IM) are work horse of power industries. Controlling of IM is crucial task in most of the applications. This paper presents implementation of a Variable Frequency Drive (VFD) controller for a three phase induction motor driven by single phase supply on an Arduino platform. The hardware setup involves a rectifier-inverter combination along with a DC link. The present work concentrates on programming the timers of ATMEGA 2560 microcontroller to obtain the required switching pulses. The simulation results of the developed switching control technique with due validation from a hardware setup are presented.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133176822","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 : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9277495
T. Santhosh Kumar, J. Shanmugam
Nowadays, the improvement of power quality is the major concern in power system scenario. As per literature analysis so far a huge number of technique implemented to improve power quality of the system. Out of these, the FACTS controllers plays a key role. This paper is presents a concept of series and shunt active filters implemented with 9-level inverters to reduce the harmonic distortions. The series active filter control structure is implemented with system and load voltages, the reference currents required for shunt active filter is implemented using PQ-control theory. To get better improvement of power quality and harmonic distortion, the series and shunt controllers are implemented with CUCKOO controller. This proposed system is tested and verified in MATLAB/SIMULINK.
{"title":"Application of Cuckoo Controller to 9-Level NPC based APF to Improve Power Quality","authors":"T. Santhosh Kumar, J. Shanmugam","doi":"10.1109/ICSTCEE49637.2020.9277495","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9277495","url":null,"abstract":"Nowadays, the improvement of power quality is the major concern in power system scenario. As per literature analysis so far a huge number of technique implemented to improve power quality of the system. Out of these, the FACTS controllers plays a key role. This paper is presents a concept of series and shunt active filters implemented with 9-level inverters to reduce the harmonic distortions. The series active filter control structure is implemented with system and load voltages, the reference currents required for shunt active filter is implemented using PQ-control theory. To get better improvement of power quality and harmonic distortion, the series and shunt controllers are implemented with CUCKOO controller. This proposed system is tested and verified in MATLAB/SIMULINK.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127794230","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 : 2020-10-09DOI: 10.1109/ICSTCEE49637.2020.9277076
Zabiha Khan, R. Loganathan
Gastrointestinal (GI) cancer consists of a group of ten cancers that affect the various accessory organs of the digestive system and liver cancer is one of them. In India, it is ranked twelfth in terms of new cases, eight in terms of deaths and increasing as per the Global cancer Observatory data of last year. Like other cancers, it can be cured if detected early. But the diagnostic performance of Computerized Tomography (CT) images for Liver cancer is interpreter-dependent and prone to human errors. Medical image segmentation and analysis of tumor can help in Computer-aided diagnosis (CAD). Automatic Segmenting of liver and tumor is a complex task as it depends on the shape, location, texture and intensity. Therefore, to develop a general-purpose algorithm that fits all is not possible. Both these tasks can be performed either manually or in a semi-automated manner. In this paper we present AutoLiv, automated liver-tumor detection in CT images. In the first stage, threshold-based slope difference differentiation (SDD) technique is used for segmentation of liver and using this in the second stage we carry out tumor detection by alternative fuzzy c-means (AFCM) clustering algorithm. MATLAB based results and manual segmentation results are compared. A close correlation is observed between both the manual and automated approach with very high degree of spatial overlap seen in the regions-of-interest (ROIs) isolated by both methods.
{"title":"AutoLiv: Automated Liver Tumor Segmentation in CT Images","authors":"Zabiha Khan, R. Loganathan","doi":"10.1109/ICSTCEE49637.2020.9277076","DOIUrl":"https://doi.org/10.1109/ICSTCEE49637.2020.9277076","url":null,"abstract":"Gastrointestinal (GI) cancer consists of a group of ten cancers that affect the various accessory organs of the digestive system and liver cancer is one of them. In India, it is ranked twelfth in terms of new cases, eight in terms of deaths and increasing as per the Global cancer Observatory data of last year. Like other cancers, it can be cured if detected early. But the diagnostic performance of Computerized Tomography (CT) images for Liver cancer is interpreter-dependent and prone to human errors. Medical image segmentation and analysis of tumor can help in Computer-aided diagnosis (CAD). Automatic Segmenting of liver and tumor is a complex task as it depends on the shape, location, texture and intensity. Therefore, to develop a general-purpose algorithm that fits all is not possible. Both these tasks can be performed either manually or in a semi-automated manner. In this paper we present AutoLiv, automated liver-tumor detection in CT images. In the first stage, threshold-based slope difference differentiation (SDD) technique is used for segmentation of liver and using this in the second stage we carry out tumor detection by alternative fuzzy c-means (AFCM) clustering algorithm. MATLAB based results and manual segmentation results are compared. A close correlation is observed between both the manual and automated approach with very high degree of spatial overlap seen in the regions-of-interest (ROIs) isolated by both methods.","PeriodicalId":113845,"journal":{"name":"2020 International Conference on Smart Technologies in Computing, Electrical and Electronics (ICSTCEE)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-10-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130573518","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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