Pub Date : 1900-01-01DOI: 10.1109/ICCCSP.2017.7944087
N. Sangeetha, K. Anusudha
Digital image processing techniques are commonly used to enhance an image to extract the useful information from it. Images acquired by a visual system are seriously degraded under hazy and foggy weather, which will affect the detection, tracking, and recognition of targets. The degraded images have reduced contrast and the local information is lost. Thus, restoring the true scene from such a foggy image is of significance. The paper focuses on enhancing the contrast and visibility of the foggy image by using various enhancement techniques. The performance of the proposed techniques are analyzed based on standard parameters.
{"title":"Image defogging using enhancement techniques","authors":"N. Sangeetha, K. Anusudha","doi":"10.1109/ICCCSP.2017.7944087","DOIUrl":"https://doi.org/10.1109/ICCCSP.2017.7944087","url":null,"abstract":"Digital image processing techniques are commonly used to enhance an image to extract the useful information from it. Images acquired by a visual system are seriously degraded under hazy and foggy weather, which will affect the detection, tracking, and recognition of targets. The degraded images have reduced contrast and the local information is lost. Thus, restoring the true scene from such a foggy image is of significance. The paper focuses on enhancing the contrast and visibility of the foggy image by using various enhancement techniques. The performance of the proposed techniques are analyzed based on standard parameters.","PeriodicalId":269595,"journal":{"name":"2017 International Conference on Computer, Communication and Signal Processing (ICCCSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131202474","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 : 1900-01-01DOI: 10.1109/ICCCSP.2017.7944072
Jayaram Hariharakrishnan, S. Mohanavalli, Srividya, K. Kumar
Big Data analytics has become important as many administrations, organizations, and companies both public and private have been collecting and analyzing huge amounts of domain-specific information, which can contain useful information about problems such as national intelligence, cyber security, fraud detection, marketing, and medical informatics. With more and more data being generated the ever dynamic size, scale, diversity, and complexity has made the requirement for newer architectures, techniques, algorithms, and analytics to manage it and extract value from the data collected. The progress and innovation is no longer hindered by the ability to collect data but, by the ability to manage, analyze, summarize, visualize, and discover knowledge from the collected data in a timely manner and in a scalable fashion as well as a credible clean and noise free data sets. This paper mainly makes an attempt to understand the different problems to solve in the processes of data preprocessing, to also familiarize with the problems related to cleaning data, know the problems to apply data cleaning and noise removal techniques for big data analytics and to mitigate the imperfect data, together with some techniques to solve them and also to identify the shortcomings in the existing methods of the reduction techniques in the necessary respective areas of application and also to identify the current big data preprocessing proposal's effectiveness to various data sets.
{"title":"Survey of pre-processing techniques for mining big data","authors":"Jayaram Hariharakrishnan, S. Mohanavalli, Srividya, K. Kumar","doi":"10.1109/ICCCSP.2017.7944072","DOIUrl":"https://doi.org/10.1109/ICCCSP.2017.7944072","url":null,"abstract":"Big Data analytics has become important as many administrations, organizations, and companies both public and private have been collecting and analyzing huge amounts of domain-specific information, which can contain useful information about problems such as national intelligence, cyber security, fraud detection, marketing, and medical informatics. With more and more data being generated the ever dynamic size, scale, diversity, and complexity has made the requirement for newer architectures, techniques, algorithms, and analytics to manage it and extract value from the data collected. The progress and innovation is no longer hindered by the ability to collect data but, by the ability to manage, analyze, summarize, visualize, and discover knowledge from the collected data in a timely manner and in a scalable fashion as well as a credible clean and noise free data sets. This paper mainly makes an attempt to understand the different problems to solve in the processes of data preprocessing, to also familiarize with the problems related to cleaning data, know the problems to apply data cleaning and noise removal techniques for big data analytics and to mitigate the imperfect data, together with some techniques to solve them and also to identify the shortcomings in the existing methods of the reduction techniques in the necessary respective areas of application and also to identify the current big data preprocessing proposal's effectiveness to various data sets.","PeriodicalId":269595,"journal":{"name":"2017 International Conference on Computer, Communication and Signal Processing (ICCCSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114505548","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 : 1900-01-01DOI: 10.1109/ICCCSP.2017.7944064
H. Habiba, T. Prashanth, S. Keerthipriya, L. N. A. Sayeed, R. Sandhya
A compact fullmode SIW UWBband pass filter using novel input/output transmission-line-structure is proposed in this paper. This wide band SIW resonator can be evolved from a conventional SIW transmission lineor a two-conductor transmission line. This filter has wide passband of 3–8GHz with return loss of nearly −20dB.
{"title":"A compact full mode SIW UWB Band pass filter using novel input/output transmission-line-stnicture","authors":"H. Habiba, T. Prashanth, S. Keerthipriya, L. N. A. Sayeed, R. Sandhya","doi":"10.1109/ICCCSP.2017.7944064","DOIUrl":"https://doi.org/10.1109/ICCCSP.2017.7944064","url":null,"abstract":"A compact fullmode SIW UWBband pass filter using novel input/output transmission-line-structure is proposed in this paper. This wide band SIW resonator can be evolved from a conventional SIW transmission lineor a two-conductor transmission line. This filter has wide passband of 3–8GHz with return loss of nearly −20dB.","PeriodicalId":269595,"journal":{"name":"2017 International Conference on Computer, Communication and Signal Processing (ICCCSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127331231","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 : 1900-01-01DOI: 10.1109/ICCCSP.2017.7944061
N. Moratanch, S. Chitrakala
Text Summarization is the process of obtaining salient information from an authentic text document. In this technique, the extracted information is achieved as a summarized report and conferred as a concise summary to the user. It is very crucial for humans to understand and to describe the content of the text. Text Summarization techniques are classified into abstractive and extractive summarization. The extractive summarization technique focuses on choosing how paragraphs, important sentences, etc produces the original documents in precise form. The implication of sentences is determined based on linguistic and statistical features. In this work, a comprehensive review of extractive text summarization process methods has been ascertained. In this paper, the various techniques, populous benchmarking datasets and challenges of extractive summarization have been reviewed. This paper interprets extractive text summarization methods with a less redundant summary, highly adhesive, coherent and depth information.
{"title":"A survey on extractive text summarization","authors":"N. Moratanch, S. Chitrakala","doi":"10.1109/ICCCSP.2017.7944061","DOIUrl":"https://doi.org/10.1109/ICCCSP.2017.7944061","url":null,"abstract":"Text Summarization is the process of obtaining salient information from an authentic text document. In this technique, the extracted information is achieved as a summarized report and conferred as a concise summary to the user. It is very crucial for humans to understand and to describe the content of the text. Text Summarization techniques are classified into abstractive and extractive summarization. The extractive summarization technique focuses on choosing how paragraphs, important sentences, etc produces the original documents in precise form. The implication of sentences is determined based on linguistic and statistical features. In this work, a comprehensive review of extractive text summarization process methods has been ascertained. In this paper, the various techniques, populous benchmarking datasets and challenges of extractive summarization have been reviewed. This paper interprets extractive text summarization methods with a less redundant summary, highly adhesive, coherent and depth information.","PeriodicalId":269595,"journal":{"name":"2017 International Conference on Computer, Communication and Signal Processing (ICCCSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127495331","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 : 1900-01-01DOI: 10.1109/ICCCSP.2017.7944073
L. Pavithra, T. Sharmila
This paper proposes a new chrominance feature extraction method in HMMD color space. Image dependent multi-level thresholding is performed in the HMMD color space to obtain the 64-IeveI quantized images. The occurrence count of each color pixel represents the color information of those quantized images. This technique is tested over Wang's database of 10 different category images. The distance measure of this feature between the query and database image are calculated. Then, the proposed method performance is evaluated using average precision and recall. Moreover, the proposed method is a benchmark against the state-of-the-art color feature extraction methods and gives approximately 6.3% to 18.05% and 7.54% to 14.52 % high precision and recall than the conventional techniques.
{"title":"Image retrieval based on chrominance feature of the HMMD color space","authors":"L. Pavithra, T. Sharmila","doi":"10.1109/ICCCSP.2017.7944073","DOIUrl":"https://doi.org/10.1109/ICCCSP.2017.7944073","url":null,"abstract":"This paper proposes a new chrominance feature extraction method in HMMD color space. Image dependent multi-level thresholding is performed in the HMMD color space to obtain the 64-IeveI quantized images. The occurrence count of each color pixel represents the color information of those quantized images. This technique is tested over Wang's database of 10 different category images. The distance measure of this feature between the query and database image are calculated. Then, the proposed method performance is evaluated using average precision and recall. Moreover, the proposed method is a benchmark against the state-of-the-art color feature extraction methods and gives approximately 6.3% to 18.05% and 7.54% to 14.52 % high precision and recall than the conventional techniques.","PeriodicalId":269595,"journal":{"name":"2017 International Conference on Computer, Communication and Signal Processing (ICCCSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114693375","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 : 1900-01-01DOI: 10.1109/ICCCSP.2017.7944082
J. Julina, T. Sharmila
Face recognition is widely used in computer vision and in many other biometric applications where security is a major concern. The most common problem in recognizing a face arises due to pose variations, different illumination conditions and so on. The main focus of this paper is to recognize whether a given face input corresponds to a registered person in the database. Face recognition is done using Histogram of Oriented Gradients (HOG) technique in AT & T database with an inclusion of a real time subject to evaluate the performance of the algorithm. The feature vectors generated by HOG descriptor are used to train Support Vector Machines (SVM) and results are verified against a given test input. The proposed method checks whether a test image in different pose and lighting conditions is matched correctly with trained images of the facial database. The results of the proposed approach show minimal false positives and improved detection accuracy.
{"title":"Facial recognition using histogram of gradients and support vector machines","authors":"J. Julina, T. Sharmila","doi":"10.1109/ICCCSP.2017.7944082","DOIUrl":"https://doi.org/10.1109/ICCCSP.2017.7944082","url":null,"abstract":"Face recognition is widely used in computer vision and in many other biometric applications where security is a major concern. The most common problem in recognizing a face arises due to pose variations, different illumination conditions and so on. The main focus of this paper is to recognize whether a given face input corresponds to a registered person in the database. Face recognition is done using Histogram of Oriented Gradients (HOG) technique in AT & T database with an inclusion of a real time subject to evaluate the performance of the algorithm. The feature vectors generated by HOG descriptor are used to train Support Vector Machines (SVM) and results are verified against a given test input. The proposed method checks whether a test image in different pose and lighting conditions is matched correctly with trained images of the facial database. The results of the proposed approach show minimal false positives and improved detection accuracy.","PeriodicalId":269595,"journal":{"name":"2017 International Conference on Computer, Communication and Signal Processing (ICCCSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114720345","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 : 1900-01-01DOI: 10.1109/ICCCSP.2017.7944085
R. M. Brigitta, P. Samundiswary
In recent years, wireless networking plays a prominent role because of its easy installation and flexibility. Among the various wireless domains, Zigbee based Wireless Dynamic Sensor Networks (WDSN) pose a good support to the dynamics that arise when the nodes are induced with mobility. In the Zigbee based Wireless Dynamic Sensor Network (WDSN), major consideration is on utilizing the energy efficiently among the mobile nodes. Various techniques are used to attain energy efficiency in Zigbee WDSN. Among them, clustering the nodes is one of the best methods, since they aim at reducing the energy dissipation and increasing the life span of the network. Hence, in this paper, the performance of Zigbee WDSN using clustering scheme is done by considering the nodes with mobility and compared with performance of Zigbee WDSN using non clustering technique. The proposed work is summarized as follows: the network is deployed as clusters and the remaining energy of the node is determined by utilizing clustering protocol. In each cluster, the clustering protocol opts for the node with the maximum remaining energy as the head of that cluster. Then STR algorithm is utilized to route the sensed data from the member nodes to the cluster head. Hence, the clustering technique and STR, route the information through the shortest path paving the way for enhanced average residual energy and Packet Delivery Ratio (PDR). The simulations are done by using ns2 and performance metrics such as average residual energy and PDR are computed and analyzed for non clustered and clustered method.
{"title":"Performance analysis of Zigbee WDSN using clustering protocol and STR algorithm","authors":"R. M. Brigitta, P. Samundiswary","doi":"10.1109/ICCCSP.2017.7944085","DOIUrl":"https://doi.org/10.1109/ICCCSP.2017.7944085","url":null,"abstract":"In recent years, wireless networking plays a prominent role because of its easy installation and flexibility. Among the various wireless domains, Zigbee based Wireless Dynamic Sensor Networks (WDSN) pose a good support to the dynamics that arise when the nodes are induced with mobility. In the Zigbee based Wireless Dynamic Sensor Network (WDSN), major consideration is on utilizing the energy efficiently among the mobile nodes. Various techniques are used to attain energy efficiency in Zigbee WDSN. Among them, clustering the nodes is one of the best methods, since they aim at reducing the energy dissipation and increasing the life span of the network. Hence, in this paper, the performance of Zigbee WDSN using clustering scheme is done by considering the nodes with mobility and compared with performance of Zigbee WDSN using non clustering technique. The proposed work is summarized as follows: the network is deployed as clusters and the remaining energy of the node is determined by utilizing clustering protocol. In each cluster, the clustering protocol opts for the node with the maximum remaining energy as the head of that cluster. Then STR algorithm is utilized to route the sensed data from the member nodes to the cluster head. Hence, the clustering technique and STR, route the information through the shortest path paving the way for enhanced average residual energy and Packet Delivery Ratio (PDR). The simulations are done by using ns2 and performance metrics such as average residual energy and PDR are computed and analyzed for non clustered and clustered method.","PeriodicalId":269595,"journal":{"name":"2017 International Conference on Computer, Communication and Signal Processing (ICCCSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114896693","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 : 1900-01-01DOI: 10.1109/ICCCSP.2017.7944069
A. Beulah, T. Sharmila
Image segmentation is well known in partitioning a digital image into several segments. Recent days lower back pain in human being increases and so the lumber spine pathology detection becomes a predominant research area in Computer Aided Diagnosis (CAD) system. In the process of lumbar spine pathology detection, the segmentation of the Intervertebral Disc (IVD) is the major step as it identifies the IVDs or the boundaries of the IVDs either normal or abnormal in images. When the axial or the sagittal View of lumbar spine MR image is given as input, this proposed work segments the IVD in both the axial and sagittal views. The segmentation of IVD is a four stage process. First, Expectation-Maximization (EM) segmentation is performed on the MR Image. EM segmentation yields an advantage over K-means with the case of the size of clustering. The second stage is to carry out the morphological operators and third, apply edge detection method and obtain the edges. The final stage is to remove unwanted objects from the obtained output image. If this proposed segmentation is utilized as part of the CAD, the experts will be benefited for localizing the IVD and to diagnose the IVD disease.
{"title":"EM algorithm based intervertebral disc segmentation on MR images","authors":"A. Beulah, T. Sharmila","doi":"10.1109/ICCCSP.2017.7944069","DOIUrl":"https://doi.org/10.1109/ICCCSP.2017.7944069","url":null,"abstract":"Image segmentation is well known in partitioning a digital image into several segments. Recent days lower back pain in human being increases and so the lumber spine pathology detection becomes a predominant research area in Computer Aided Diagnosis (CAD) system. In the process of lumbar spine pathology detection, the segmentation of the Intervertebral Disc (IVD) is the major step as it identifies the IVDs or the boundaries of the IVDs either normal or abnormal in images. When the axial or the sagittal View of lumbar spine MR image is given as input, this proposed work segments the IVD in both the axial and sagittal views. The segmentation of IVD is a four stage process. First, Expectation-Maximization (EM) segmentation is performed on the MR Image. EM segmentation yields an advantage over K-means with the case of the size of clustering. The second stage is to carry out the morphological operators and third, apply edge detection method and obtain the edges. The final stage is to remove unwanted objects from the obtained output image. If this proposed segmentation is utilized as part of the CAD, the experts will be benefited for localizing the IVD and to diagnose the IVD disease.","PeriodicalId":269595,"journal":{"name":"2017 International Conference on Computer, Communication and Signal Processing (ICCCSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128734606","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 : 1900-01-01DOI: 10.1109/ICCCSP.2017.7944107
D. V. Ranganathan, R. Vishal, V. Krishnamurthy, Prashant Mahesh, Roopeshwar Devarajan
Many multiplayer card games have interesting structures that can be exploited while designing a computer application to simulate these games. Critical features that most games have are that they are turn based and have common data types like Cards and Decks. This paper aims to demonstrate certain design patterns for implementing multiplayer card games that are capable of scaling well and are easily understandable and maintainable. Two card games ‘Ace’ and ‘Literature’ were developed from which the patterns were extracted. The patterns explained in this paper, can be applied to any turn-based multiplayer card game and in some cases, to any multiplayer game in general. The two patterns discussed in this paper are represented in small caps to have better understanding.
{"title":"Design patterns for multiplayer card games","authors":"D. V. Ranganathan, R. Vishal, V. Krishnamurthy, Prashant Mahesh, Roopeshwar Devarajan","doi":"10.1109/ICCCSP.2017.7944107","DOIUrl":"https://doi.org/10.1109/ICCCSP.2017.7944107","url":null,"abstract":"Many multiplayer card games have interesting structures that can be exploited while designing a computer application to simulate these games. Critical features that most games have are that they are turn based and have common data types like Cards and Decks. This paper aims to demonstrate certain design patterns for implementing multiplayer card games that are capable of scaling well and are easily understandable and maintainable. Two card games ‘Ace’ and ‘Literature’ were developed from which the patterns were extracted. The patterns explained in this paper, can be applied to any turn-based multiplayer card game and in some cases, to any multiplayer game in general. The two patterns discussed in this paper are represented in small caps to have better understanding.","PeriodicalId":269595,"journal":{"name":"2017 International Conference on Computer, Communication and Signal Processing (ICCCSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130963419","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 : 1900-01-01DOI: 10.1109/ICCCSP.2017.7944084
J. Jennifer, T. Sharmila
Living in an information age the whole earth is a small globe in our hands with the advancements of computers, smartphones etc. The usage of computers in our day-to-day activities has increased enormously leading to both positive and negative effects in our lives. The negative effects are related to health problems such as Computer Vision Syndrome (CVS) etc. Prolonged use of computers would lead to a significant reduction of spontaneous eye blink rate due to the high visual demand of the screen and concentration on the work. The proposed system develops a prototype using blink as a solution to prevent CVS. The first part of the work captures video frames using web-camera mounted on the computer or laptop. These frames are processed dynamically by cropping only the eyes. The algorithms performed on the eye-frames are direct pixel count, gradient. Canny edge and Laplacian of Gaussian (LoG). These determine the eye-status based on the threshold value and the proposed idea, the difference between upper and lower eye frames. Various experiments are done and their algorithms are compared and concluded that the proposed algorithm yields 99.95% accuracy.
{"title":"Edge based eye-blink detection for computer vision syndrome","authors":"J. Jennifer, T. Sharmila","doi":"10.1109/ICCCSP.2017.7944084","DOIUrl":"https://doi.org/10.1109/ICCCSP.2017.7944084","url":null,"abstract":"Living in an information age the whole earth is a small globe in our hands with the advancements of computers, smartphones etc. The usage of computers in our day-to-day activities has increased enormously leading to both positive and negative effects in our lives. The negative effects are related to health problems such as Computer Vision Syndrome (CVS) etc. Prolonged use of computers would lead to a significant reduction of spontaneous eye blink rate due to the high visual demand of the screen and concentration on the work. The proposed system develops a prototype using blink as a solution to prevent CVS. The first part of the work captures video frames using web-camera mounted on the computer or laptop. These frames are processed dynamically by cropping only the eyes. The algorithms performed on the eye-frames are direct pixel count, gradient. Canny edge and Laplacian of Gaussian (LoG). These determine the eye-status based on the threshold value and the proposed idea, the difference between upper and lower eye frames. Various experiments are done and their algorithms are compared and concluded that the proposed algorithm yields 99.95% accuracy.","PeriodicalId":269595,"journal":{"name":"2017 International Conference on Computer, Communication and Signal Processing (ICCCSP)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123955518","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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