Pub Date : 2020-07-03DOI: 10.1109/ICSCAN49426.2020.9262359
K. Dhivya, G. Premalatha, M. Kayathri
An ophthalmic disease that affects the retinal blood vessels called diabetic retinopathy. The diabetic retinopathy results in vision loss. A diabetic retinopathy is not treated in primitive stages may lead to vision loss. The diabetic retinopathy has five different classes. They are normal, mild, moderate, secure, PDR. Generally, highly trained people process the colored fundus image to treat the fatal disease. The manual analysis, and detecting of diabetic retinopathy is complex and even error occurred in results. The manual detection takes long time to diagnose the DR. Using the different computer-based techniques have been used to detect the DR and it shows the retinal blood vessels but it does not differentiate the early stages and unable to process the tedious features. The results from computer vision based gives low accuracy. In this project, Artificial Neural Network (ANN) is used to classify various stages of Diabetic retinopathy. The results obtained from that shows better accuracy and performance.
{"title":"Automated Identification of Diabetic Retinopathy Using Artificial Neutral Network","authors":"K. Dhivya, G. Premalatha, M. Kayathri","doi":"10.1109/ICSCAN49426.2020.9262359","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262359","url":null,"abstract":"An ophthalmic disease that affects the retinal blood vessels called diabetic retinopathy. The diabetic retinopathy results in vision loss. A diabetic retinopathy is not treated in primitive stages may lead to vision loss. The diabetic retinopathy has five different classes. They are normal, mild, moderate, secure, PDR. Generally, highly trained people process the colored fundus image to treat the fatal disease. The manual analysis, and detecting of diabetic retinopathy is complex and even error occurred in results. The manual detection takes long time to diagnose the DR. Using the different computer-based techniques have been used to detect the DR and it shows the retinal blood vessels but it does not differentiate the early stages and unable to process the tedious features. The results from computer vision based gives low accuracy. In this project, Artificial Neural Network (ANN) is used to classify various stages of Diabetic retinopathy. The results obtained from that shows better accuracy and performance.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"27 5","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91471506","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 : 2020-07-03DOI: 10.1109/ICSCAN49426.2020.9262364
R. Kalyani, P. Sathya, V. Sakthivel, J. Ravikumar
The most fundamental step in image processing is image segmentation and it results in revealing enormous information embedded in most widely used RGB color space image. Excellent result is obtained for bi-level thresholding and the exhaustive search for optimal threshold values, to analyze complex images in multilevel thresholding (MLT), is reduced by promising objective functions such as Otsu and minimum cross entropy MCE aided with teaching-learning based optimization metaheuristic algorithm (TLBO). In TLBO, a teacher shares cognizance to a student. The use of only common control parameters and less-specific control parameters in TLBO achieves exploration and exploitation. The efficiency of TLBO is compared with cuckoo search algorithm (CS) at 4,5,6 and 7 threshold levels. Experimental results reveal that optimal output of TLBO is more successful in precise image segmentation and aids in various real time applications.
{"title":"Teaching Tactics for Color Image Segmentation Using Otsu and Minimum Cross Entropy","authors":"R. Kalyani, P. Sathya, V. Sakthivel, J. Ravikumar","doi":"10.1109/ICSCAN49426.2020.9262364","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262364","url":null,"abstract":"The most fundamental step in image processing is image segmentation and it results in revealing enormous information embedded in most widely used RGB color space image. Excellent result is obtained for bi-level thresholding and the exhaustive search for optimal threshold values, to analyze complex images in multilevel thresholding (MLT), is reduced by promising objective functions such as Otsu and minimum cross entropy MCE aided with teaching-learning based optimization metaheuristic algorithm (TLBO). In TLBO, a teacher shares cognizance to a student. The use of only common control parameters and less-specific control parameters in TLBO achieves exploration and exploitation. The efficiency of TLBO is compared with cuckoo search algorithm (CS) at 4,5,6 and 7 threshold levels. Experimental results reveal that optimal output of TLBO is more successful in precise image segmentation and aids in various real time applications.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"27 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79426778","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}
According to reports, an astounding 69% of adult drivers report driving while drowsy at least once a month in the previous year according to The National Sleep Foundation. In today's fast-moving world people are usually stressed and sleep-deprived due to their demanding career. As a result of this such people fall asleep behind the wheel. Visual fatigue and drowsiness cause many accidents due to which many deaths and injuries are taking place around the world. To increase vehicle security, we propose an advanced driver assistance system (ADAS). This system aims to locate and estimate the driver's eye condition and head position using a camera that will be an indication of his drowsiness level. We also propose a speed control system to detect signboards on the way and instruct the driver either to continue with the same speed or to decelerate the vehicle based on machine learning. This system also calculates the distance between two vehicles, based on the distance it instructs the driver either to continue with the same speed or to slow down. With the system on board of multiple vehicles the safety of the travel increases and the rate of accidents caused due to driver negligence will be reduced.
{"title":"Neural Network Based Driver Warning System","authors":"Ishan Jain, Snehangsu Biswas, Hrishita Singh, Prakriti Aggarwal","doi":"10.1109/ICSCAN49426.2020.9262325","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262325","url":null,"abstract":"According to reports, an astounding 69% of adult drivers report driving while drowsy at least once a month in the previous year according to The National Sleep Foundation. In today's fast-moving world people are usually stressed and sleep-deprived due to their demanding career. As a result of this such people fall asleep behind the wheel. Visual fatigue and drowsiness cause many accidents due to which many deaths and injuries are taking place around the world. To increase vehicle security, we propose an advanced driver assistance system (ADAS). This system aims to locate and estimate the driver's eye condition and head position using a camera that will be an indication of his drowsiness level. We also propose a speed control system to detect signboards on the way and instruct the driver either to continue with the same speed or to decelerate the vehicle based on machine learning. This system also calculates the distance between two vehicles, based on the distance it instructs the driver either to continue with the same speed or to slow down. With the system on board of multiple vehicles the safety of the travel increases and the rate of accidents caused due to driver negligence will be reduced.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"41 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82022050","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 : 2020-07-03DOI: 10.1109/ICSCAN49426.2020.9262435
M. Suresh, A. S, P. V, M. A.
This paper proposes the development of intelligent street lights that minimizes the wastage of power by applying the method of reliable smart mangement proposal that is essential for a wealthy lifestyle for upcoming generations living in modern platform. The propsoed model involves three main stages namely maintenence stage, automatic adaptive ON/OFF control stage and prediction of electricity consumption stage. In order to apply this technique, a Wi-Fi module, Light dependent sensor (LDR), accelerometer and ultrasonic sensors are employed. The accelerometer sensor is utilized for identifying the pole inclination and report the emergency condition to control room or user. Then, LDR sensor is employed to turn ON-OFF of street lights with respect to atmosphere intensity level. This switching could be performed using ESP8266 based on the LDR. Ultrasonic sensor helps to sense the presence of any vechicle or person in a specified range, then light glows with 100% brightness else, it is reduced and glow with only with the intensity of 60%. Besides, a predictive model based on imporved bayesian neural netwok (IBNN) model is applied. The need of IBNN model is to report the utilization of the power for a period of specific duration. The propsoed work eliminates the power wastage during night time if there is no vechicle or trespassers passing. Moreover, by applying these three sensors, an intelligent automatic light is developed using IoT frame work that is effective.
{"title":"An Intelligent Smart Street Light System with Predictive model","authors":"M. Suresh, A. S, P. V, M. A.","doi":"10.1109/ICSCAN49426.2020.9262435","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262435","url":null,"abstract":"This paper proposes the development of intelligent street lights that minimizes the wastage of power by applying the method of reliable smart mangement proposal that is essential for a wealthy lifestyle for upcoming generations living in modern platform. The propsoed model involves three main stages namely maintenence stage, automatic adaptive ON/OFF control stage and prediction of electricity consumption stage. In order to apply this technique, a Wi-Fi module, Light dependent sensor (LDR), accelerometer and ultrasonic sensors are employed. The accelerometer sensor is utilized for identifying the pole inclination and report the emergency condition to control room or user. Then, LDR sensor is employed to turn ON-OFF of street lights with respect to atmosphere intensity level. This switching could be performed using ESP8266 based on the LDR. Ultrasonic sensor helps to sense the presence of any vechicle or person in a specified range, then light glows with 100% brightness else, it is reduced and glow with only with the intensity of 60%. Besides, a predictive model based on imporved bayesian neural netwok (IBNN) model is applied. The need of IBNN model is to report the utilization of the power for a period of specific duration. The propsoed work eliminates the power wastage during night time if there is no vechicle or trespassers passing. Moreover, by applying these three sensors, an intelligent automatic light is developed using IoT frame work that is effective.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"53 1","pages":"1-4"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88877950","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 : 2020-07-03DOI: 10.1109/ICSCAN49426.2020.9262376
B.V.K. Namratha, S. U. Devi
Shoulder surfing is one of the major problem in today's world as any intruder can easily hack the data from our mobile phone and most of the people store all the confidential details in mobile phone by which they can easily access the data as the keypad consist only a numerical values i.e. from 0 to 9.This paper exhibits the prevention of shoulder surfing in E-Wallet to solve the problem of shoulder surfing in the E-Wallet a technique which consists of colours or graphical method in place of the numerical values which is proposed earlier. The graphical method uses the colours in place of the numbers in keypad with the help of neuro fuzzy algorithm. The neuro fuzzy algorithm is mainly proposed for interchanging the colours. Neuro fuzzy algorithm is executed in wamp server as it is used for web improvement and inner testing. Wamp server uses a php and SQL and also access less space for any type of computation. The proposed method of shoulder surfing has improved the efficiency and security for the E-Wallet as it may be difficult for the gate crasher to assume the code using graphical representation method.
{"title":"Prediction of Shoulder Surfing in E-Wallet","authors":"B.V.K. Namratha, S. U. Devi","doi":"10.1109/ICSCAN49426.2020.9262376","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262376","url":null,"abstract":"Shoulder surfing is one of the major problem in today's world as any intruder can easily hack the data from our mobile phone and most of the people store all the confidential details in mobile phone by which they can easily access the data as the keypad consist only a numerical values i.e. from 0 to 9.This paper exhibits the prevention of shoulder surfing in E-Wallet to solve the problem of shoulder surfing in the E-Wallet a technique which consists of colours or graphical method in place of the numerical values which is proposed earlier. The graphical method uses the colours in place of the numbers in keypad with the help of neuro fuzzy algorithm. The neuro fuzzy algorithm is mainly proposed for interchanging the colours. Neuro fuzzy algorithm is executed in wamp server as it is used for web improvement and inner testing. Wamp server uses a php and SQL and also access less space for any type of computation. The proposed method of shoulder surfing has improved the efficiency and security for the E-Wallet as it may be difficult for the gate crasher to assume the code using graphical representation method.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"110 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85795603","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 : 2020-07-03DOI: 10.1109/ICSCAN49426.2020.9262329
Parth Koltharkar, Eldhose K K, R. Sridharan
With globalization and an increase in population, education has a significant role in the economic well-being of a nation. Due to this reason, the quality of education offered by educational institutes has become significant. The quality of education is judged differently by different stakeholders. In the present study, students are considered as stakeholders who are experiencing the service of the education system. Socialization has led to the hype of students' expectations / requirements / interest in techno-managerial education. Through literature review, internet search and focus groups study, 8 dimensions (major interest) and 40 items (minor interest) are identified. Fuzzy TOPSIS approach is adopted to prioritize the items of each dimension by considering the vagueness in the responses received from the students of a higher education institution in South India. This prioritization will aid the institute to focus on top priority parameters in which they are lagging and also maintain the service level of moderate and low priority parameters.
{"title":"Application of fuzzy TOPSIS for the prioritization of students' requirements in higher education institutions: a case study : A multi-criteria decision making approach","authors":"Parth Koltharkar, Eldhose K K, R. Sridharan","doi":"10.1109/ICSCAN49426.2020.9262329","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262329","url":null,"abstract":"With globalization and an increase in population, education has a significant role in the economic well-being of a nation. Due to this reason, the quality of education offered by educational institutes has become significant. The quality of education is judged differently by different stakeholders. In the present study, students are considered as stakeholders who are experiencing the service of the education system. Socialization has led to the hype of students' expectations / requirements / interest in techno-managerial education. Through literature review, internet search and focus groups study, 8 dimensions (major interest) and 40 items (minor interest) are identified. Fuzzy TOPSIS approach is adopted to prioritize the items of each dimension by considering the vagueness in the responses received from the students of a higher education institution in South India. This prioritization will aid the institute to focus on top priority parameters in which they are lagging and also maintain the service level of moderate and low priority parameters.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"40 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85841192","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 : 2020-07-03DOI: 10.1109/ICSCAN49426.2020.9262404
Rohit Kumar, A. B. Bazil Raj
This In this work a new algorithm for the system in which space i.e. size is main concern is proposed. Using this algorithm we can achieve desired accuracy and preciseness in range calculation of a system, even when power is a big concern i.e. altimeter or other range equipment. For the verification of algorithm it is implemented in experimental setup with FPGA in altimeter range equipment. The range for the same has been also verified using virtual GUIs. The range verification using the designed algorithm has been verified for smaller to large scale variations and found appropriate for calibrated and measured range. The algorithm has been implemented using VHDL code in Modelsim/ISIM simulator. Results of proposed algorithm are compared with the existed architecture and reduction in chip area and delay has been observed.
{"title":"Customized Floating Point Algorithm for the Ranging System","authors":"Rohit Kumar, A. B. Bazil Raj","doi":"10.1109/ICSCAN49426.2020.9262404","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262404","url":null,"abstract":"This In this work a new algorithm for the system in which space i.e. size is main concern is proposed. Using this algorithm we can achieve desired accuracy and preciseness in range calculation of a system, even when power is a big concern i.e. altimeter or other range equipment. For the verification of algorithm it is implemented in experimental setup with FPGA in altimeter range equipment. The range for the same has been also verified using virtual GUIs. The range verification using the designed algorithm has been verified for smaller to large scale variations and found appropriate for calibrated and measured range. The algorithm has been implemented using VHDL code in Modelsim/ISIM simulator. Results of proposed algorithm are compared with the existed architecture and reduction in chip area and delay has been observed.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"423 1","pages":"1-7"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86847156","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 : 2020-07-03DOI: 10.1109/ICSCAN49426.2020.9262352
K. Muninathan, M. Venkataramanan, P. R. Daison Jacob, K. Gnanasekar, K. Gowtham
This paper analyses different stacking position and wood size to obtain the most effective parameters to obtain maximum yield from the chosen plant, which is Prosopis juliflora. It is available abundantly and has the ability to grow at an astounding rate. Proximate analysis is used to determine the composition of wood and charcoal obtained. Charcoal is extracted from wood by subjecting it to pyrolysis process at a temperature of 400°C for 4 hours. Conical, Vertical cylinder, Horizontal cylinder, Vertical square, Horizontal square and Cross stacking are six types of stacking arrangement and twigs, logs and roots are the three wood sizes which are chosen for the experiment. Two trials were conducted to find the efficient stacking position. Among the stacking arrangement Vertical cylinder stacking was chosen to be more efficient with a good yield of 24.1% and less unburnt wood of 0.3%. Four trials were conducted to identify the most efficient wood size. Among the wood sizes roots are found to be more efficient with the highest yield of 34%. This is due high moisture and low ash content of roots.
{"title":"Effect of Wood Size and Stacking on Pyrolysis Process using Prosopis Juliflora","authors":"K. Muninathan, M. Venkataramanan, P. R. Daison Jacob, K. Gnanasekar, K. Gowtham","doi":"10.1109/ICSCAN49426.2020.9262352","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262352","url":null,"abstract":"This paper analyses different stacking position and wood size to obtain the most effective parameters to obtain maximum yield from the chosen plant, which is Prosopis juliflora. It is available abundantly and has the ability to grow at an astounding rate. Proximate analysis is used to determine the composition of wood and charcoal obtained. Charcoal is extracted from wood by subjecting it to pyrolysis process at a temperature of 400°C for 4 hours. Conical, Vertical cylinder, Horizontal cylinder, Vertical square, Horizontal square and Cross stacking are six types of stacking arrangement and twigs, logs and roots are the three wood sizes which are chosen for the experiment. Two trials were conducted to find the efficient stacking position. Among the stacking arrangement Vertical cylinder stacking was chosen to be more efficient with a good yield of 24.1% and less unburnt wood of 0.3%. Four trials were conducted to identify the most efficient wood size. Among the wood sizes roots are found to be more efficient with the highest yield of 34%. This is due high moisture and low ash content of roots.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"76 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"87290535","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 : 2020-07-03DOI: 10.1109/ICSCAN49426.2020.9262305
M. Giridhar, Lasin, V. V. Panicker
This research explores different ways of presenting material and information at workstations, using various assembly scenarios with fifteen subjects and six different types of pen. Use of intermixed parts, grouped parts, separated parts in different boxes, and part numbered box is the material presentation factors and information presentation factor involve text instructions and photographs. It can be inferred from the results that the number of parts assembled is higher when using part numbered box with instructions and with the least errors. However, using intermixed parts with instructions resulted in a decreased number of pens assembled. The assembly time provided for each subject was ten minutes. It is found that the workload and the stress factor in identifying the parts, distinguishing and assembling during the intermixed and grouped parts with instructions got reduced in the further scenarios. Work station design and planning can be done based on the cognitive skills of subjects, and according to their skills the various material and information presentation factors can be prepared. This results in effective utilization of manpower which leads to improved productivity and effectiveness.
{"title":"Experimental analysis of cognitive issues impacting manual assembly task","authors":"M. Giridhar, Lasin, V. V. Panicker","doi":"10.1109/ICSCAN49426.2020.9262305","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262305","url":null,"abstract":"This research explores different ways of presenting material and information at workstations, using various assembly scenarios with fifteen subjects and six different types of pen. Use of intermixed parts, grouped parts, separated parts in different boxes, and part numbered box is the material presentation factors and information presentation factor involve text instructions and photographs. It can be inferred from the results that the number of parts assembled is higher when using part numbered box with instructions and with the least errors. However, using intermixed parts with instructions resulted in a decreased number of pens assembled. The assembly time provided for each subject was ten minutes. It is found that the workload and the stress factor in identifying the parts, distinguishing and assembling during the intermixed and grouped parts with instructions got reduced in the further scenarios. Work station design and planning can be done based on the cognitive skills of subjects, and according to their skills the various material and information presentation factors can be prepared. This results in effective utilization of manpower which leads to improved productivity and effectiveness.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"39 1","pages":"1-6"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85364127","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 : 2020-07-03DOI: 10.1109/ICSCAN49426.2020.9262390
S. Ayyappan, S. Matilda
Face recognition is a biometric based technology that maps an individual's facial features mathematically and stores the data as a face print. It employs Machine Learning on the image and generates a feature vector which maps an object with array of numbers. This technology is used by organizations such as Google and Facebook to create a digital profile for its users. This project proposes to use this technology for identifying criminals who are on the run from their previous records. An NCRB (National Crime Records Bureau) report shows that 70% of crimes are repeatedly committed by the same criminals. These criminals can be identified by the face recognition from an image or video frame which is captured by the cameras which are installed in various locations and it can also be used for identifying missing children. The disadvantage posed is that the images are usually blurred, have less clarity and not recognizable to the human eye. The proposed system can successfully recognize more than one face which is useful for quickly searching suspected persons as the computation time is very low. It creates a unique template for each face and compare them with other images available in dataset. If the match is found for the input face, then the details associated with the related image will be displayed. This system will decrease the crimes and ensure the security in our society.
{"title":"Criminals And Missing Children Identification Using Face Recognition And Web Scrapping","authors":"S. Ayyappan, S. Matilda","doi":"10.1109/ICSCAN49426.2020.9262390","DOIUrl":"https://doi.org/10.1109/ICSCAN49426.2020.9262390","url":null,"abstract":"Face recognition is a biometric based technology that maps an individual's facial features mathematically and stores the data as a face print. It employs Machine Learning on the image and generates a feature vector which maps an object with array of numbers. This technology is used by organizations such as Google and Facebook to create a digital profile for its users. This project proposes to use this technology for identifying criminals who are on the run from their previous records. An NCRB (National Crime Records Bureau) report shows that 70% of crimes are repeatedly committed by the same criminals. These criminals can be identified by the face recognition from an image or video frame which is captured by the cameras which are installed in various locations and it can also be used for identifying missing children. The disadvantage posed is that the images are usually blurred, have less clarity and not recognizable to the human eye. The proposed system can successfully recognize more than one face which is useful for quickly searching suspected persons as the computation time is very low. It creates a unique template for each face and compare them with other images available in dataset. If the match is found for the input face, then the details associated with the related image will be displayed. This system will decrease the crimes and ensure the security in our society.","PeriodicalId":6744,"journal":{"name":"2020 International Conference on System, Computation, Automation and Networking (ICSCAN)","volume":"43 1","pages":"1-5"},"PeriodicalIF":0.0,"publicationDate":"2020-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84216784","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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