In recent years, research on iris recognition in near-infrared has made great progress and achievements. However in many devices, such as most of the mobile phones, there is no near-infrared device embedded. In order to use iris recognition in these devices, iris recognition in visible light is needed, but there are many problems to use visible iris recognition, including low recognition rate, poor robustness and so on. In this paper, we first clarified the challenges in visible iris recognition. We evaluate the effectiveness of three traditional iris recognition on iris collected from smart phones in visible light. The results show that traditional methods achieve accuracy not exceeding 60% at best. Then we summarize the recent advances in visible iris recognition in three aspects: iris image acquisition, iris preprocessing and iris feature extraction methods. In the end, we list future research directions in visible iris recognition.
{"title":"A SURVEY OF VISIBLE IRIS RECOGNITION","authors":"Yali Song, Yong-Xin He, Jin Zhang","doi":"10.5121/CSIT.2019.90302","DOIUrl":"https://doi.org/10.5121/CSIT.2019.90302","url":null,"abstract":"In recent years, research on iris recognition in near-infrared has made great progress and achievements. However in many devices, such as most of the mobile phones, there is no near-infrared device embedded. In order to use iris recognition in these devices, iris recognition in visible light is needed, but there are many problems to use visible iris recognition, including low recognition rate, poor robustness and so on. In this paper, we first clarified the challenges in visible iris recognition. We evaluate the effectiveness of three traditional iris recognition on iris collected from smart phones in visible light. The results show that traditional methods achieve accuracy not exceeding 60% at best. Then we summarize the recent advances in visible iris recognition in three aspects: iris image acquisition, iris preprocessing and iris feature extraction methods. In the end, we list future research directions in visible iris recognition.","PeriodicalId":372948,"journal":{"name":"Computer Science & Information Technology (CS & IT )","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134038367","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}
{"title":"Simplification of Compiler Design Course Teaching Using Concept Maps","authors":"V. Subramanian, K. Natarajan","doi":"10.5121/CSIT.2019.90309","DOIUrl":"https://doi.org/10.5121/CSIT.2019.90309","url":null,"abstract":"","PeriodicalId":372948,"journal":{"name":"Computer Science & Information Technology (CS & IT )","volume":"59 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126283885","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}
Ivo Socrates M. de Oliveira, O. C. Linares, Ary Henrique M. de Oliveira, G. Botelho, J. E. S. B. Neto
Despite the large number of techniques and applications in the field of image segmentation, it is still an open research field. A recent trend in image segmentation is the usage of graph theory. This work proposes an approach which combines community detection in multiplex networks, in which a layer represents a certain image feature, with super pixels. There are approaches for the segmentation of images of good quality that use a single feature or the combination of several features of the image forming a single graph for the detection of communities and the segmentation. However, with the use of multiplex networks it is possible to use more than one image feature without the need for mathematical operations that can lead to the loss of information of the image features during the generation of the graphs. Through the related experiments, presented in this work, it is possible to identify that such method can offer quality and robust segmentations.
{"title":"IMAGE SEGMENTATION BASED ON MULTIPLEX NETWORKS AND SUPER PIXELS","authors":"Ivo Socrates M. de Oliveira, O. C. Linares, Ary Henrique M. de Oliveira, G. Botelho, J. E. S. B. Neto","doi":"10.5121/CSIT.2019.90304","DOIUrl":"https://doi.org/10.5121/CSIT.2019.90304","url":null,"abstract":"Despite the large number of techniques and applications in the field of image segmentation, it is still an open research field. A recent trend in image segmentation is the usage of graph theory. This work proposes an approach which combines community detection in multiplex networks, in which a layer represents a certain image feature, with super pixels. There are approaches for the segmentation of images of good quality that use a single feature or the combination of several features of the image forming a single graph for the detection of communities and the segmentation. However, with the use of multiplex networks it is possible to use more than one image feature without the need for mathematical operations that can lead to the loss of information of the image features during the generation of the graphs. Through the related experiments, presented in this work, it is possible to identify that such method can offer quality and robust segmentations.","PeriodicalId":372948,"journal":{"name":"Computer Science & Information Technology (CS & IT )","volume":"124 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124195522","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}
Suyeol Kim, Chaehwan Hwang, Jisu Kim, Cheolhyeong Park, Deokwoo Lee
Sleep apnea is considered one of the most critical problems of human health, and it is also considered one of the most important bio-signals in the area of medicine. In this paper, we propose the approach to detection and classification of respiratory status based on cross correlation between normal respiration and apnea, and on the characteristics of respiratory signals. The characteristics of the signals are extracted by analyzing frequency analysis. The proposed method is simple and straightforward so that it can be workable in practice. To substantiate the proposed algorithm, the experimental results are provided.
{"title":"SIMILARITY BASED CLASSIFICATION AND DETECTION OF RESPIRATORY STATUS IN FREQUENCY DOMAIN","authors":"Suyeol Kim, Chaehwan Hwang, Jisu Kim, Cheolhyeong Park, Deokwoo Lee","doi":"10.5121/CSIT.2019.90301","DOIUrl":"https://doi.org/10.5121/CSIT.2019.90301","url":null,"abstract":"Sleep apnea is considered one of the most critical problems of human health, and it is also considered one of the most important bio-signals in the area of medicine. In this paper, we propose the approach to detection and classification of respiratory status based on cross correlation between normal respiration and apnea, and on the characteristics of respiratory signals. The characteristics of the signals are extracted by analyzing frequency analysis. The proposed method is simple and straightforward so that it can be workable in practice. To substantiate the proposed algorithm, the experimental results are provided.","PeriodicalId":372948,"journal":{"name":"Computer Science & Information Technology (CS & IT )","volume":"54 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128479801","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}
The 21st century came with its own challenges as much as it brought various benefits through the advancement in technology. Cultural heritage is one such “casualty” of the developments in the 21st century in that there has been a decline in appreciation and awareness of the importance of cultural heritage. Thus, the present study was necessitated with the primary aim of (i) preservation of the intangible cultural heritage of the people of Georgetown through the development of the E-George Town Digital Heritage (E-GDH) system (ii) develop an effective GUI for the E-DGH system in order to stimulate and captivate the attention of users with the aim of raising awareness as well to educate the masses on the importance of cultural heritage and (iii) to evaluate the effectiveness of the developed system in relation to its objective through the administration of questionnaires to target respondents. To this effect the study employed the use of the waterfall model to develop this E-GDH website. The study found that respondents (prior to using the E-GDH system) had no previous experience in terms of oral story telling from their parents. Overall, it was found that the GUI was pleasant and attractive for use by respondents and that they were able to learn easily as a result. Based on the fact that respondents where able to learn with ease due to an effective GUI, the study also revealed that the content they were learning from this website was actually easy for them to understand and that this website was indeed helpful in helping them to understand and appreciate cultural heritage. The meaning and conduct of the education sector in this era of advanced technology has shifted a lot over the years changing from teachers as the primary source of information to what is termed as “learner –centred” where they are given the leeway to learn, explore and make sense of the world around them and the findings from this study falls no short from this notion. The E-GDH website could be used by schools in subjects such as history where the teacher could use this website as reference point for a certain lesson outcome that deals with digital cultural heritage or intangible cultural heritage. Thus the study contributes immensely to the understanding of cultural heritage by raising awareness as well as stimulating the inters of the young generation to appreciate and learn more about their cultural heritage. The prominence of digitalising the intangible cultural heritage cannot be emphasised enough as recent study has shown decline in interests in these area so the development of the E-GDH is one such positive call to action in response to UNESCO’s 2003 call for preservation of intangible cultural heritage and by extension, educating and raising awareness on the importance of cultural heritage.
{"title":"A BASIS OF CULTURAL EDUCATION: SAFEGUARDING INTANGIBLE HERITAGE THROUGH A WEB-BASED DIGITAL PHOTOGRAPHIC COLLECTION","authors":"C. Lim, K. Tan, Nguarije Hambira","doi":"10.5121/CSIT.2019.90311","DOIUrl":"https://doi.org/10.5121/CSIT.2019.90311","url":null,"abstract":"The 21st century came with its own challenges as much as it brought various benefits through the advancement in technology. Cultural heritage is one such “casualty” of the developments in the 21st century in that there has been a decline in appreciation and awareness of the importance of cultural heritage. Thus, the present study was necessitated with the primary aim of (i) preservation of the intangible cultural heritage of the people of Georgetown through the development of the E-George Town Digital Heritage (E-GDH) system (ii) develop an effective GUI for the E-DGH system in order to stimulate and captivate the attention of users with the aim of raising awareness as well to educate the masses on the importance of cultural heritage and (iii) to evaluate the effectiveness of the developed system in relation to its objective through the administration of questionnaires to target respondents. To this effect the study employed the use of the waterfall model to develop this E-GDH website. The study found that respondents (prior to using the E-GDH system) had no previous experience in terms of oral story telling from their parents. Overall, it was found that the GUI was pleasant and attractive for use by respondents and that they were able to learn easily as a result. Based on the fact that respondents where able to learn with ease due to an effective GUI, the study also revealed that the content they were learning from this website was actually easy for them to understand and that this website was indeed helpful in helping them to understand and appreciate cultural heritage. The meaning and conduct of the education sector in this era of advanced technology has shifted a lot over the years changing from teachers as the primary source of information to what is termed as “learner –centred” where they are given the leeway to learn, explore and make sense of the world around them and the findings from this study falls no short from this notion. The E-GDH website could be used by schools in subjects such as history where the teacher could use this website as reference point for a certain lesson outcome that deals with digital cultural heritage or intangible cultural heritage. Thus the study contributes immensely to the understanding of cultural heritage by raising awareness as well as stimulating the inters of the young generation to appreciate and learn more about their cultural heritage. The prominence of digitalising the intangible cultural heritage cannot be emphasised enough as recent study has shown decline in interests in these area so the development of the E-GDH is one such positive call to action in response to UNESCO’s 2003 call for preservation of intangible cultural heritage and by extension, educating and raising awareness on the importance of cultural heritage.","PeriodicalId":372948,"journal":{"name":"Computer Science & Information Technology (CS & IT )","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132795083","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}
This paper chiefly focuses on calibration of depth camera system, particularly on stereo camera. Owing to complexity of parameter estimation of camera, i.e., it is an inverse problem the calibration is still challenging problem in computer vision. As similar to the previous method of the calibration, checkerboard is used in this work. However, corner detection is carried out by employing the concept of neural network. Since the corner detection of the previous work depends on the exterior environment such as ambient light, quality of the checkerboard itself, etc., learning of the geometric characteristics of the corners are conducted. The pro-posed method detects a region of checkboard from the captured images (a pair of images), and the corners are detected. Detection accuracy is increased by calculating the weights of the deep neural network. The procedure of the detection is de-tailed in this paper. The quantitative evaluation of the method is shown by calculating the re-projection error. Comparison is performed with the most popular method, Zhang’s calibration one. The experimental results not only validate the accuracy of the calibration, but also shows the efficiency of the calibration.
{"title":"GEOMETRIC DEEP LEARNED FEATURE CLASSIFICATION BASED CAMERA CALIBRATION","authors":"Cheolhyeong Park, Jisu Kim, Deokwoo Lee","doi":"10.5121/CSIT.2019.90305","DOIUrl":"https://doi.org/10.5121/CSIT.2019.90305","url":null,"abstract":"This paper chiefly focuses on calibration of depth camera system, particularly on stereo camera. Owing to complexity of parameter estimation of camera, i.e., it is an inverse problem the calibration is still challenging problem in computer vision. As similar to the previous method of the calibration, checkerboard is used in this work. However, corner detection is carried out by employing the concept of neural network. Since the corner detection of the previous work depends on the exterior environment such as ambient light, quality of the checkerboard itself, etc., learning of the geometric characteristics of the corners are conducted. The pro-posed method detects a region of checkboard from the captured images (a pair of images), and the corners are detected. Detection accuracy is increased by calculating the weights of the deep neural network. The procedure of the detection is de-tailed in this paper. The quantitative evaluation of the method is shown by calculating the re-projection error. Comparison is performed with the most popular method, Zhang’s calibration one. The experimental results not only validate the accuracy of the calibration, but also shows the efficiency of the calibration.","PeriodicalId":372948,"journal":{"name":"Computer Science & Information Technology (CS & IT )","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128839962","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}
The number of services and smart devices which require context is increasing, and there is a clear need for new security policies which provide security that is convenient and flexible for the user. In particular, there is an urgent need for new security policies regarding IT vulnerability layers for children, the elderly, and the disabled who experience many difficulties using current security technology. For a convenient and flexible security policy, it is necessary to collect and analyze data such as user service use patterns, locations, etc., which can be used to distinguish attack contexts and define a security service provision technology which is suitable to the user. This study has designed a user context-aware network security architecture which reflects the aforementioned requirements, collected user context-aware data, studied a user context analysis platform, and studied and analyzed context-aware security applications.
{"title":"NETWORK SECURITY ARCHITECTURE AND APPLICATIONS BASED ON CONTEXT-AWARE SECURITY","authors":"Hoon Ko, Chang Choi, Pankoo Kim, Junho Choi","doi":"10.5121/CSIT.2019.90308","DOIUrl":"https://doi.org/10.5121/CSIT.2019.90308","url":null,"abstract":"The number of services and smart devices which require context is increasing, and there is a clear need for new security policies which provide security that is convenient and flexible for the user. In particular, there is an urgent need for new security policies regarding IT vulnerability layers for children, the elderly, and the disabled who experience many difficulties using current security technology. For a convenient and flexible security policy, it is necessary to collect and analyze data such as user service use patterns, locations, etc., which can be used to distinguish attack contexts and define a security service provision technology which is suitable to the user. This study has designed a user context-aware network security architecture which reflects the aforementioned requirements, collected user context-aware data, studied a user context analysis platform, and studied and analyzed context-aware security applications.","PeriodicalId":372948,"journal":{"name":"Computer Science & Information Technology (CS & IT )","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126472380","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}
Graph databases and distributed graph computing systems have traditionally abstracted the design and execution of algorithms by encouraging users to take the perspective of lone graph objects, like vertices and edges. In this paper, we introduce the SmartGraph, a graph database that instead relies upon thinking like a smarter device often found in real-life computer networks, the router. Unlike existing methodologies that work at the subgraph level, the SmartGraph is implemented as a network of artificially intelligent Communicating Sequential Processes. The primary goal of this design is to give each “router” a large degree of autonomy. We demonstrate how this design facilitates the formulation and solution of an optimization problem which we refer to as the “router representation problem”, wherein each router selects a beneficial graph data structure according to its individual requirements (including its local data structure, and the operations requested of it). We demonstrate a solution to the router representation problem wherein the combinatorial global optimization problem with exponential complexity is reduced to a series of linear problems locally solvable by each AI router.
{"title":"SMARTGRAPH: AN ARTIFICIALLY INTELLIGENT GRAPH DATABASE","authors":"H. Cooper, G. Iyengar, Ching-Yung Lin","doi":"10.5121/CSIT.2019.90307","DOIUrl":"https://doi.org/10.5121/CSIT.2019.90307","url":null,"abstract":"Graph databases and distributed graph computing systems have traditionally abstracted the design and execution of algorithms by encouraging users to take the perspective of lone graph objects, like vertices and edges. In this paper, we introduce the SmartGraph, a graph database that instead relies upon thinking like a smarter device often found in real-life computer networks, the router. Unlike existing methodologies that work at the subgraph level, the SmartGraph is implemented as a network of artificially intelligent Communicating Sequential Processes. The primary goal of this design is to give each “router” a large degree of autonomy. We demonstrate how this design facilitates the formulation and solution of an optimization problem which we refer to as the “router representation problem”, wherein each router selects a beneficial graph data structure according to its individual requirements (including its local data structure, and the operations requested of it). We demonstrate a solution to the router representation problem wherein the combinatorial global optimization problem with exponential complexity is reduced to a series of linear problems locally solvable by each AI router.","PeriodicalId":372948,"journal":{"name":"Computer Science & Information Technology (CS & IT )","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127753922","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}
Image segmentation is a fundamental step in the modern computational vision systems and its goal is to produce amore simple and meaningful representation of the image making it easier to analyze. Imagesegmentation is a subcategory of image processing ofdigital images and, basically, it divides a given image into two parts: the object(s) of interest and the background. Image segmentation is typically used to locate objects and boundaries in images and its applicability extends to other methods such as classification, feature extraction and pattern recognition. Most methods are based on histogram analysis, edge detection and region-growing. Currently, other approaches are presented such as segmentation by graph partition, using genetic algorithms and genetic programming. This paper presents a review of this area, starting with taxonomy of the methods followed by a discussion of the most relevant ones.
{"title":"EVALUATION OF DIFFERENT IMAGE SEGMENTATION METHODS WITH RESPECT TO COMPUTATIONAL SYSTEMS","authors":"MehakSaini, K. Saini","doi":"10.5121/CSIT.2019.90306","DOIUrl":"https://doi.org/10.5121/CSIT.2019.90306","url":null,"abstract":"Image segmentation is a fundamental step in the modern computational vision systems and its goal is to produce amore simple and meaningful representation of the image making it easier to analyze. Imagesegmentation is a subcategory of image processing ofdigital images and, basically, it divides a given image into two parts: the object(s) of interest and the background. Image segmentation is typically used to locate objects and boundaries in images and its applicability extends to other methods such as classification, feature extraction and pattern recognition. Most methods are based on histogram analysis, edge detection and region-growing. Currently, other approaches are presented such as segmentation by graph partition, using genetic algorithms and genetic programming. This paper presents a review of this area, starting with taxonomy of the methods followed by a discussion of the most relevant ones.","PeriodicalId":372948,"journal":{"name":"Computer Science & Information Technology (CS & IT )","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132102862","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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