Pub Date : 2019-01-01DOI: 10.1109/ICISC44355.2019.9036389
Akshatha N, K. Rai, H. K, Rachita Ramesh, Rajeshwari Hegde, Sharath Kumar
Tactile internet is a potential, emerging technology that will play a crucial role in the enhancement of the way human senses interact with machines. This paper presents the technology concepts of the Tactile Internet. The requirements are discussed in brief followed by the architecture, emphasizing the Network Design and Mobile Edge Cloud. The applications with respect to the latest innovations revolving around smart cities, haptic applications, and other IoT applications are outlined. Advances in 5G technology are expected to pave the way for ambitious improvements in future communications especially those pertaining to scalability, throughput, capacity, security, and latency. The paper accentuates the impact and applications of the Tactile Internet on the lives of humans in the years to come with the merging of the two technologies and their fusion with Artificial Intelligence.
{"title":"Tactile Internet: Next Generation IoT","authors":"Akshatha N, K. Rai, H. K, Rachita Ramesh, Rajeshwari Hegde, Sharath Kumar","doi":"10.1109/ICISC44355.2019.9036389","DOIUrl":"https://doi.org/10.1109/ICISC44355.2019.9036389","url":null,"abstract":"Tactile internet is a potential, emerging technology that will play a crucial role in the enhancement of the way human senses interact with machines. This paper presents the technology concepts of the Tactile Internet. The requirements are discussed in brief followed by the architecture, emphasizing the Network Design and Mobile Edge Cloud. The applications with respect to the latest innovations revolving around smart cities, haptic applications, and other IoT applications are outlined. Advances in 5G technology are expected to pave the way for ambitious improvements in future communications especially those pertaining to scalability, throughput, capacity, security, and latency. The paper accentuates the impact and applications of the Tactile Internet on the lives of humans in the years to come with the merging of the two technologies and their fusion with Artificial Intelligence.","PeriodicalId":419157,"journal":{"name":"2019 Third International Conference on Inventive Systems and Control (ICISC)","volume":"87 2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116736590","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 : 2019-01-01DOI: 10.1109/ICISC44355.2019.9036342
Mrityunjaya D Hatagundi, Amruta Navadagi, G. Sadashivappa
It has been observed in the recent decade that there has been a huge demand for the Radio wave communication. On the other side, optical communication getting special attention of researchers since it facilitates System Reliability, Higher data rates, Enormous Bandwidth availability, Electrical isolation etc. When we combine both types of communication discussed above, the resulting system would be the best communication system. Traditional systems used normal light wave to modulate other light waves. In this paper a special system that makes use of Radio waves to modulate light signals. Radio over Fibre (RoF) or RF over Fibre (RFoF) is a method of optical communication is a linearization technique used in order to reduce nonlinear distortion and increase receiver sensitivity. The reader is expected to have sound knowledge of Optical Communication Networks and Radio wave communication.
{"title":"Implementation of Broadband Radio over Fibre (RoF) Passive Optical Networks (PON) using Optisystem","authors":"Mrityunjaya D Hatagundi, Amruta Navadagi, G. Sadashivappa","doi":"10.1109/ICISC44355.2019.9036342","DOIUrl":"https://doi.org/10.1109/ICISC44355.2019.9036342","url":null,"abstract":"It has been observed in the recent decade that there has been a huge demand for the Radio wave communication. On the other side, optical communication getting special attention of researchers since it facilitates System Reliability, Higher data rates, Enormous Bandwidth availability, Electrical isolation etc. When we combine both types of communication discussed above, the resulting system would be the best communication system. Traditional systems used normal light wave to modulate other light waves. In this paper a special system that makes use of Radio waves to modulate light signals. Radio over Fibre (RoF) or RF over Fibre (RFoF) is a method of optical communication is a linearization technique used in order to reduce nonlinear distortion and increase receiver sensitivity. The reader is expected to have sound knowledge of Optical Communication Networks and Radio wave communication.","PeriodicalId":419157,"journal":{"name":"2019 Third International Conference on Inventive Systems and Control (ICISC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125386084","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 : 2019-01-01DOI: 10.1109/ICISC44355.2019.9036460
T. Murthy, N. Gopalan, V. Ramachandran
Availability of electric power has been the most essential source in acquiring industrial, social and economic developments in any state in India. Every day the Power distribution systems face new challenges to estimate the technical and commercial losses. Apart from technical losses, there are non-technical losses like electricity theft, vandalism to electrical substations, poor meter reading and improper accounting etc. In this work the non-technical losses are investigated by the end user abnormalities in power distribution system using data mining techniques, so that the transmission and distribution losses along the lines will be detected quickly and hence reduced. The model consists of two stages. In the first stage Fuzzy c-Means technique is widely used clustering technique to combine group of end users with homogeneous consumption profiles and to eliminate customers of abnormal consumption profiles. In the second stage a fine tuned classification technique, Naive Bayes is applied. The distances between clusters are measured by using the Euclidean distance, the maximum usage identifies as fraudsters. The proposed technique was tested on the real time data lead to defect detection compared record of respective electricity distribution system. Experimental results signify that the cascaded Fuzzy C-Means and Naive Bayes have enhanced the classification accuracy.
{"title":"A Naive Bayes Classifier for Detecting Unusual Customer Consumption Profiles in Power Distribution Systems - APSPDCL","authors":"T. Murthy, N. Gopalan, V. Ramachandran","doi":"10.1109/ICISC44355.2019.9036460","DOIUrl":"https://doi.org/10.1109/ICISC44355.2019.9036460","url":null,"abstract":"Availability of electric power has been the most essential source in acquiring industrial, social and economic developments in any state in India. Every day the Power distribution systems face new challenges to estimate the technical and commercial losses. Apart from technical losses, there are non-technical losses like electricity theft, vandalism to electrical substations, poor meter reading and improper accounting etc. In this work the non-technical losses are investigated by the end user abnormalities in power distribution system using data mining techniques, so that the transmission and distribution losses along the lines will be detected quickly and hence reduced. The model consists of two stages. In the first stage Fuzzy c-Means technique is widely used clustering technique to combine group of end users with homogeneous consumption profiles and to eliminate customers of abnormal consumption profiles. In the second stage a fine tuned classification technique, Naive Bayes is applied. The distances between clusters are measured by using the Euclidean distance, the maximum usage identifies as fraudsters. The proposed technique was tested on the real time data lead to defect detection compared record of respective electricity distribution system. Experimental results signify that the cascaded Fuzzy C-Means and Naive Bayes have enhanced the classification accuracy.","PeriodicalId":419157,"journal":{"name":"2019 Third International Conference on Inventive Systems and Control (ICISC)","volume":"1996 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128226227","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 : 2019-01-01DOI: 10.1109/ICISC44355.2019.9036473
D. S, R. Vignesh, R. Revathy
The distinctive machine learning model that was created as a need for doctors/ oncologists who treat patients in critical stages. The present day has many people suffering from cancer where they get diagnosed only during the last stage (4th stage) of cancer. This leads to many untimely deaths of their loved ones for many people. To reduce such risks and provide more effort in saving those lives, this model may be used. This model is made from Random Forest classlfier[1] where it classifies a tumor to be either Benign(Non-cancerous) or Malignant(Cancerous). It uses 10 features of tumor subdivided into mean, standard error and worst case value of each to increase its accuracy. The inputs given to this model are obtained from medical imaging and hence do not need any medical tests where time may be wasted. The future of this model relies on the demand where it may lie in being developed into an application or it may be developed into a full-fledged health-care system. The main objective of this model, is to ensure that more time can be bought to save or extend the lifetime of the patient by providing chemotherapy as a preventive measure for an untimely death that may occur. This model predicts with 94.34% accuracy, 93% best case confidence and 56% worst case confidence whether the given data resembles a malignant or benign tumor.
{"title":"A Distincitve Model to Classify Tumor Using Random Forest Classifier","authors":"D. S, R. Vignesh, R. Revathy","doi":"10.1109/ICISC44355.2019.9036473","DOIUrl":"https://doi.org/10.1109/ICISC44355.2019.9036473","url":null,"abstract":"The distinctive machine learning model that was created as a need for doctors/ oncologists who treat patients in critical stages. The present day has many people suffering from cancer where they get diagnosed only during the last stage (4th stage) of cancer. This leads to many untimely deaths of their loved ones for many people. To reduce such risks and provide more effort in saving those lives, this model may be used. This model is made from Random Forest classlfier[1] where it classifies a tumor to be either Benign(Non-cancerous) or Malignant(Cancerous). It uses 10 features of tumor subdivided into mean, standard error and worst case value of each to increase its accuracy. The inputs given to this model are obtained from medical imaging and hence do not need any medical tests where time may be wasted. The future of this model relies on the demand where it may lie in being developed into an application or it may be developed into a full-fledged health-care system. The main objective of this model, is to ensure that more time can be bought to save or extend the lifetime of the patient by providing chemotherapy as a preventive measure for an untimely death that may occur. This model predicts with 94.34% accuracy, 93% best case confidence and 56% worst case confidence whether the given data resembles a malignant or benign tumor.","PeriodicalId":419157,"journal":{"name":"2019 Third International Conference on Inventive Systems and Control (ICISC)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128913956","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 : 2019-01-01DOI: 10.1109/ICISC44355.2019.9036356
Sudersan Behera
As we know that fuzzy association rules are used to convert crisp set elements in to fuzzy set elements like “height=long”. On other hand Association rules on crisp set are bounded with in a limit to transfer crisp set elements in to the binary values like “height = [5.5feet or above]” and it losses some information at boundaries because of its restricted nature. Today the variations of fuzzy association rule mining is most popular. As the crisp version of Apriori, fuzzy Apriori algorithms are quit inefficient for large volume of data sets. Hence it is required to bring an efficient and powerful FA rule mining for better performance over large volume of data sets. I f we compare the fuzzy Apriori with the proposed algorithm the proposed algorithm is almost 16% faster than the earlier one if both the algorithm compared together in case of very large data sets. The proposed algorithm also has excellent processing techniques to convert the non-fuzzy dataset into fuzzy dataset
{"title":"Knowledge Mining from Large Volume of Dataset using Fuzzy Association Rule","authors":"Sudersan Behera","doi":"10.1109/ICISC44355.2019.9036356","DOIUrl":"https://doi.org/10.1109/ICISC44355.2019.9036356","url":null,"abstract":"As we know that fuzzy association rules are used to convert crisp set elements in to fuzzy set elements like “height=long”. On other hand Association rules on crisp set are bounded with in a limit to transfer crisp set elements in to the binary values like “height = [5.5feet or above]” and it losses some information at boundaries because of its restricted nature. Today the variations of fuzzy association rule mining is most popular. As the crisp version of Apriori, fuzzy Apriori algorithms are quit inefficient for large volume of data sets. Hence it is required to bring an efficient and powerful FA rule mining for better performance over large volume of data sets. I f we compare the fuzzy Apriori with the proposed algorithm the proposed algorithm is almost 16% faster than the earlier one if both the algorithm compared together in case of very large data sets. The proposed algorithm also has excellent processing techniques to convert the non-fuzzy dataset into fuzzy dataset","PeriodicalId":419157,"journal":{"name":"2019 Third International Conference on Inventive Systems and Control (ICISC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127133026","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 : 2019-01-01DOI: 10.1109/ICISC44355.2019.9036407
Kishore Kumar, D. Shanmugam, S. Min, Murali Subramaniyam
Ageing is inevitable and leads to numerous problems including disabilities in the lower limb. Partial disabilities represent a severe challenge to many people; occur due to debilitative disorder including muscular dystrophy, accidents, stroke and other age-related issues. This problem commonly occurs in developing nations which results in lack of their development so the physiotherapist has taken many measures and recent innovation in assistive technology are very much useful. Recent developments in the field of robotics lead to the innovation of assistive devices in the rehabilitation process and assistive services. This paper gives brief literature about the methods used in assistive technology and how good they are interacting with the user. The review suggests that the human-robot interface is brought by a co-adaptive system which can be adopted by all models. The simulation process is carried out in software's like mat lab and proteus before proceeding to the hardware simulation.
{"title":"Assistive Technologies for Biologically Inspired Controller System - A Short Review Assistive Technologies for the Elderly","authors":"Kishore Kumar, D. Shanmugam, S. Min, Murali Subramaniyam","doi":"10.1109/ICISC44355.2019.9036407","DOIUrl":"https://doi.org/10.1109/ICISC44355.2019.9036407","url":null,"abstract":"Ageing is inevitable and leads to numerous problems including disabilities in the lower limb. Partial disabilities represent a severe challenge to many people; occur due to debilitative disorder including muscular dystrophy, accidents, stroke and other age-related issues. This problem commonly occurs in developing nations which results in lack of their development so the physiotherapist has taken many measures and recent innovation in assistive technology are very much useful. Recent developments in the field of robotics lead to the innovation of assistive devices in the rehabilitation process and assistive services. This paper gives brief literature about the methods used in assistive technology and how good they are interacting with the user. The review suggests that the human-robot interface is brought by a co-adaptive system which can be adopted by all models. The simulation process is carried out in software's like mat lab and proteus before proceeding to the hardware simulation.","PeriodicalId":419157,"journal":{"name":"2019 Third International Conference on Inventive Systems and Control (ICISC)","volume":"88 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122874810","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 : 2019-01-01DOI: 10.1109/ICISC44355.2019.9036367
Urvi Ajit Jere, S. Skandha, Sneh Bhat, Yashasvi R Machani, Uma Gowri S, Rajeshwari Hegde, Sharath Kumar
OSS is a collection of software and hardware which forms integrated applications. It is a group of applications that provides network planning, network management and monitoring of faults. It also supports the communication services by improving the operational activities like automating operational tasks, implement them faster and finding out the results. OSS is generally used by service designers, network planners, engineering teams, operation architect. Together with Business Support Systems (BSS) it provides various end-to-end communication services, customer facing activities, ordering, billing and support.
{"title":"Operational Support Systems for Mobile Networks","authors":"Urvi Ajit Jere, S. Skandha, Sneh Bhat, Yashasvi R Machani, Uma Gowri S, Rajeshwari Hegde, Sharath Kumar","doi":"10.1109/ICISC44355.2019.9036367","DOIUrl":"https://doi.org/10.1109/ICISC44355.2019.9036367","url":null,"abstract":"OSS is a collection of software and hardware which forms integrated applications. It is a group of applications that provides network planning, network management and monitoring of faults. It also supports the communication services by improving the operational activities like automating operational tasks, implement them faster and finding out the results. OSS is generally used by service designers, network planners, engineering teams, operation architect. Together with Business Support Systems (BSS) it provides various end-to-end communication services, customer facing activities, ordering, billing and support.","PeriodicalId":419157,"journal":{"name":"2019 Third International Conference on Inventive Systems and Control (ICISC)","volume":"34 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115195273","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 : 2019-01-01DOI: 10.1109/ICISC44355.2019.9036454
R. Abitha, S. Vennila
Autism Spectrum Disorder (ASD) is emerging as a difficult neurological disorder that have a lifetime impact on the development of different skills and talents. Recently, ASD is widely spread among many adults and children because of their food habits, changes in an environment, etc. Data Mining methods are effectively used to identify the perfect features of ASD among children and adults. Feature selection (FS) techniques are necessary for dealing with different dimensional datasets that may incorporate features in the high, little and, medium dimensions. In this paper, a comparative study of several filter feature selection techniques is utilized to diminish the size of the ASD Children dataset. Feature selection methods like SU, IG, CS and optimization technique like PSO, GA and ACO have utilized and proposed a swarm based Symmetrical Uncertainty feature selection (SSU-FS) method based on SU and PSO. For evaluating the Swarm based Symmetrical Uncertainty feature selection method (SSU-FS), classification techniques like Naïve Bayes and ANN have used.
{"title":"A Swarm Based Symmetrical Uncertainty Feature Selection Method for Autism Spectrum Disorders","authors":"R. Abitha, S. Vennila","doi":"10.1109/ICISC44355.2019.9036454","DOIUrl":"https://doi.org/10.1109/ICISC44355.2019.9036454","url":null,"abstract":"Autism Spectrum Disorder (ASD) is emerging as a difficult neurological disorder that have a lifetime impact on the development of different skills and talents. Recently, ASD is widely spread among many adults and children because of their food habits, changes in an environment, etc. Data Mining methods are effectively used to identify the perfect features of ASD among children and adults. Feature selection (FS) techniques are necessary for dealing with different dimensional datasets that may incorporate features in the high, little and, medium dimensions. In this paper, a comparative study of several filter feature selection techniques is utilized to diminish the size of the ASD Children dataset. Feature selection methods like SU, IG, CS and optimization technique like PSO, GA and ACO have utilized and proposed a swarm based Symmetrical Uncertainty feature selection (SSU-FS) method based on SU and PSO. For evaluating the Swarm based Symmetrical Uncertainty feature selection method (SSU-FS), classification techniques like Naïve Bayes and ANN have used.","PeriodicalId":419157,"journal":{"name":"2019 Third International Conference on Inventive Systems and Control (ICISC)","volume":"155 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116117623","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 : 2019-01-01DOI: 10.1109/ICISC44355.2019.9036359
V. Mekaladevi, N. Mohankumar
Driving is an activity in which all the senses have to act together and a small pain may lead to major accidents. Health monitoring system helps people suffering from chronic diseases and who needs periodic and timely medical attention. The number of deaths due to road traffic accidents has been reduced, which shows that the inventions to increase road safety have some impact. The driver's health condition is being monitored by an inbuilt nonintrusive measurement system which assures the safety precautions in a person's life. The most common problem found in real life is cardiac arrest due to various reasons like high blood pressure, high sugar level etc. Heart functioning can be monitored by extracting the ECG signal and detection is done with the Arduino UNO. When an abnormality in the acquired signal is detected, an indication is provided and then the car is stopped through CAN Trans receiver, providing a swift response. The proposed model fallouts as a low-cost solution for improving the road and vehicle safety.
{"title":"Real-time Heart Rate Abnormality Detection using ECG for Vehicle Safety","authors":"V. Mekaladevi, N. Mohankumar","doi":"10.1109/ICISC44355.2019.9036359","DOIUrl":"https://doi.org/10.1109/ICISC44355.2019.9036359","url":null,"abstract":"Driving is an activity in which all the senses have to act together and a small pain may lead to major accidents. Health monitoring system helps people suffering from chronic diseases and who needs periodic and timely medical attention. The number of deaths due to road traffic accidents has been reduced, which shows that the inventions to increase road safety have some impact. The driver's health condition is being monitored by an inbuilt nonintrusive measurement system which assures the safety precautions in a person's life. The most common problem found in real life is cardiac arrest due to various reasons like high blood pressure, high sugar level etc. Heart functioning can be monitored by extracting the ECG signal and detection is done with the Arduino UNO. When an abnormality in the acquired signal is detected, an indication is provided and then the car is stopped through CAN Trans receiver, providing a swift response. The proposed model fallouts as a low-cost solution for improving the road and vehicle safety.","PeriodicalId":419157,"journal":{"name":"2019 Third International Conference on Inventive Systems and Control (ICISC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125856568","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 : 2019-01-01DOI: 10.1109/ICISC44355.2019.9036386
P. Thejaswini, R. Srikantaswamy, A. Manjunatha
Nowadays fingerprint recognition becomes an important biometric trait for authenticating and identifying individuals. Various researchers found that there is a change in the fingerprint images due to the variation in temperature. Hence in this paper, an effective fingerprint recognition system is developed to recognize the fingerprint images varied due to environmental changes like temperature. Hence, we propose FCM-CBIR technique for the identification of fingerprint during change of temperature. In this, clustering is performed using fuzzy $mathbf{c}$ means clustering algorithm and the image retrieval process is performed using CBIR Content Based Image Retrieval. By using this proposed method, the unrecognized fingerprint due to temperature changes has been identified. The performances are measured using the various fingerprint images collected from real time environment.
{"title":"Enhanced Fingerprint Recognition by Reference Auto-correction with FCM-CBIR strategy","authors":"P. Thejaswini, R. Srikantaswamy, A. Manjunatha","doi":"10.1109/ICISC44355.2019.9036386","DOIUrl":"https://doi.org/10.1109/ICISC44355.2019.9036386","url":null,"abstract":"Nowadays fingerprint recognition becomes an important biometric trait for authenticating and identifying individuals. Various researchers found that there is a change in the fingerprint images due to the variation in temperature. Hence in this paper, an effective fingerprint recognition system is developed to recognize the fingerprint images varied due to environmental changes like temperature. Hence, we propose FCM-CBIR technique for the identification of fingerprint during change of temperature. In this, clustering is performed using fuzzy $mathbf{c}$ means clustering algorithm and the image retrieval process is performed using CBIR Content Based Image Retrieval. By using this proposed method, the unrecognized fingerprint due to temperature changes has been identified. The performances are measured using the various fingerprint images collected from real time environment.","PeriodicalId":419157,"journal":{"name":"2019 Third International Conference on Inventive Systems and Control (ICISC)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126415000","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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