Pub Date : 2012-11-01DOI: 10.1109/ISDA.2012.6416649
Nik Nur Aisyah Nik Ghazali, N. Zamani, S. Abdullah, J. Jameson
Generating a quality high resolution image has become an essential for variety purposes especially in forensic field. Compressed and at low resolution video frames of common security surveillance videos are found to be very low in clarity and degraded with many noises, distortions, blurs, bad illumination and video compression artifact. This could interfere during image interpretation and analysis process. This paper proposed a combination of super resolution methods for image processing. Using super resolution methods, high resolution image is obtained from a set of low resolution images, after it had undergone two main processes; image registration process based on Keren algorithm and image reconstruction process based on Projection onto Convex Set (POCS) on frequency domain. The validation process of output is done by calculating the Peak Signal to Noise Ratio (PSNR) value to show the comparison of image quality. The experimental results have shown that our proposed combinatorial method based super resolution and nearest neighbor methods outperformed other state-of-the-art methods.
{"title":"Super resolution combination methods for CCTV forensic interpretation","authors":"Nik Nur Aisyah Nik Ghazali, N. Zamani, S. Abdullah, J. Jameson","doi":"10.1109/ISDA.2012.6416649","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416649","url":null,"abstract":"Generating a quality high resolution image has become an essential for variety purposes especially in forensic field. Compressed and at low resolution video frames of common security surveillance videos are found to be very low in clarity and degraded with many noises, distortions, blurs, bad illumination and video compression artifact. This could interfere during image interpretation and analysis process. This paper proposed a combination of super resolution methods for image processing. Using super resolution methods, high resolution image is obtained from a set of low resolution images, after it had undergone two main processes; image registration process based on Keren algorithm and image reconstruction process based on Projection onto Convex Set (POCS) on frequency domain. The validation process of output is done by calculating the Peak Signal to Noise Ratio (PSNR) value to show the comparison of image quality. The experimental results have shown that our proposed combinatorial method based super resolution and nearest neighbor methods outperformed other state-of-the-art methods.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"143 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115277444","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 : 2012-11-01DOI: 10.1109/ISDA.2012.6416508
K. Adebayo, O. Onifade, Fatai Idowu Yisa
The continuous growth of insecurity issues around the world has further increased public interest in biometric surveillance systems. Face recognition has proven to be definitive in this area due to its low intrusiveness, accuracy and finesse unlike other biometric systems. This paper presents a comparative analysis of the performance of some selected face recognition systems, namely the PCA, 2DPCA and Artificial Neural Network. The algorithms were implemented and tested exhaustively to evaluate the performance of these algorithms under different face databases in respect to false acceptance rate and false rejection rate.
{"title":"Comparative analysis of PCA-based and Neural Network based face recognition systems","authors":"K. Adebayo, O. Onifade, Fatai Idowu Yisa","doi":"10.1109/ISDA.2012.6416508","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416508","url":null,"abstract":"The continuous growth of insecurity issues around the world has further increased public interest in biometric surveillance systems. Face recognition has proven to be definitive in this area due to its low intrusiveness, accuracy and finesse unlike other biometric systems. This paper presents a comparative analysis of the performance of some selected face recognition systems, namely the PCA, 2DPCA and Artificial Neural Network. The algorithms were implemented and tested exhaustively to evaluate the performance of these algorithms under different face databases in respect to false acceptance rate and false rejection rate.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117340735","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 : 2012-11-01DOI: 10.1109/ISDA.2012.6416628
G. Radhakrishnan, Deepa Gupta, R. Abhishek, Ankita Ajith, T. Sudarshan
Autonomous mobile robots equipped with an array of sensors are being increasingly deployed in disaster environments to assist rescue teams. The sensors attached to the robots send multimodal time series data about the disaster environments which can be analyzed to extract useful information about the environment in which the robots are deployed. A set of data mining tasks that effectively cluster various robotic environments have been investigated. The effectiveness of these data mining techniques have been demonstrated using an available robotic dataset. The accuracy of the proposed technique has been measured using a manual reference cluster set.
{"title":"Analysis of multimodal time series data of robotic environment","authors":"G. Radhakrishnan, Deepa Gupta, R. Abhishek, Ankita Ajith, T. Sudarshan","doi":"10.1109/ISDA.2012.6416628","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416628","url":null,"abstract":"Autonomous mobile robots equipped with an array of sensors are being increasingly deployed in disaster environments to assist rescue teams. The sensors attached to the robots send multimodal time series data about the disaster environments which can be analyzed to extract useful information about the environment in which the robots are deployed. A set of data mining tasks that effectively cluster various robotic environments have been investigated. The effectiveness of these data mining techniques have been demonstrated using an available robotic dataset. The accuracy of the proposed technique has been measured using a manual reference cluster set.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"399 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115202326","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 : 2012-11-01DOI: 10.1109/ISDA.2012.6416670
Megumi Maekawa, Kazuhiko Takahashi, M. Hashimoto
This paper evaluates human emotional change by sound stimuli focused on chord progression in jazz music and conducts computational emotion classification from physiological information. Psychological experiments using chord progression tunes as sound stimuli are conducted with 117 subjects and the result of subjective evaluation shows that positive emotional valance chord progression tunes that have ascending fourth aroused positive images, and negative emotional valence chord progression tunes that have chromatic descent aroused negative images. Psychophysical experiments using chord progression tunes to excite emotions in subjects are conducted to gather acceleration plethysmogram data. For computational emotion classification, multi-layer neural network using feature values extracted from heart rate and acceleration plethysmogram is used to discriminate emotional class. In experiments of computational emotion classification, an average of 38.3% classification rate is attained in three emotions - positive, negative, and neutral.
{"title":"Remarks on computational emotion classification from physiological signal - Evaluation of how jazz music chord progression influences emotion","authors":"Megumi Maekawa, Kazuhiko Takahashi, M. Hashimoto","doi":"10.1109/ISDA.2012.6416670","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416670","url":null,"abstract":"This paper evaluates human emotional change by sound stimuli focused on chord progression in jazz music and conducts computational emotion classification from physiological information. Psychological experiments using chord progression tunes as sound stimuli are conducted with 117 subjects and the result of subjective evaluation shows that positive emotional valance chord progression tunes that have ascending fourth aroused positive images, and negative emotional valence chord progression tunes that have chromatic descent aroused negative images. Psychophysical experiments using chord progression tunes to excite emotions in subjects are conducted to gather acceleration plethysmogram data. For computational emotion classification, multi-layer neural network using feature values extracted from heart rate and acceleration plethysmogram is used to discriminate emotional class. In experiments of computational emotion classification, an average of 38.3% classification rate is attained in three emotions - positive, negative, and neutral.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"237 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116097831","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 : 2012-11-01DOI: 10.1109/ISDA.2012.6416534
P. K. De, Debaroti Das
Techniques for ranking simple fuzzy numbers are abundant in nature. However, we lack effective methods for ranking intuitionistic fuzzy numbers(IFN). The aim of this paper is to introduce a new ranking procedure for trapezoidal intuitionistic fuzzy number(TRIFN). To serve the purpose, the value and ambiguity index of TRIFNs have been defined. In order to rank TRIFNs, we have defined a ranking function by taking sum of value and ambiguity index. To illustrate the the proposed ranking method a numerical example has been given.
{"title":"Ranking of trapezoidal intuitionistic fuzzy numbers","authors":"P. K. De, Debaroti Das","doi":"10.1109/ISDA.2012.6416534","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416534","url":null,"abstract":"Techniques for ranking simple fuzzy numbers are abundant in nature. However, we lack effective methods for ranking intuitionistic fuzzy numbers(IFN). The aim of this paper is to introduce a new ranking procedure for trapezoidal intuitionistic fuzzy number(TRIFN). To serve the purpose, the value and ambiguity index of TRIFNs have been defined. In order to rank TRIFNs, we have defined a ranking function by taking sum of value and ambiguity index. To illustrate the the proposed ranking method a numerical example has been given.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122111814","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 : 2012-11-01DOI: 10.1109/ISDA.2012.6416631
Satish Gajawada, Durga Toshniwal
Clustering has been used in literature to enhance classification accuracy. But most partitional clustering methods need the number of clusters as input and also they are sensitive to initialization. Although hierarchical clustering methods may be more effective in finding clustering structure of the dataset than partitional methods but hierarchical clustering methods give tree structure known as dendrogram which is a sequence of clustering solutions. Hence hierarchical clustering algorithms are not generally applied in the preprocessing step to classification methods. This problem can be solved by cutting the dendrogram to get single clustering solution. In this paper we propose a framework for classification which uses Optimal Clustering Genetic Algorithm (OCGA) to obtain optimal level of cutting the dendrogram. A single clustering solution is obtained by cutting the dendrogram at optimal level. The clusters obtained are used to enhance classification accuracy of the classification methods. The proposed classification methods have been applied for the diagnosis of diabetes disease.
{"title":"A framework for classification using genetic algorithm based clustering","authors":"Satish Gajawada, Durga Toshniwal","doi":"10.1109/ISDA.2012.6416631","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416631","url":null,"abstract":"Clustering has been used in literature to enhance classification accuracy. But most partitional clustering methods need the number of clusters as input and also they are sensitive to initialization. Although hierarchical clustering methods may be more effective in finding clustering structure of the dataset than partitional methods but hierarchical clustering methods give tree structure known as dendrogram which is a sequence of clustering solutions. Hence hierarchical clustering algorithms are not generally applied in the preprocessing step to classification methods. This problem can be solved by cutting the dendrogram to get single clustering solution. In this paper we propose a framework for classification which uses Optimal Clustering Genetic Algorithm (OCGA) to obtain optimal level of cutting the dendrogram. A single clustering solution is obtained by cutting the dendrogram at optimal level. The clusters obtained are used to enhance classification accuracy of the classification methods. The proposed classification methods have been applied for the diagnosis of diabetes disease.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129450772","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 : 2012-11-01DOI: 10.1109/ISDA.2012.6416520
Z. Suraj
The aim of this paper is to present a new methodology for knowledge representation and reasoning based on generalised fuzzy Petri nets. Recently, this net model has been proposed as a new class of fuzzy Petri nets. The new class extends the existing fuzzy Petri nets by introducing two operators: t-norms and s-norms, which are supposed to function as substitute for the min and max operators. This model is more flexible than the traditional one as in the former class the user has the chance to define the input/output operators. The choice of suitable operators for a given reasoning process and the speed of reasoning process are very important, especially in real-time decision support systems. The advantages of the proposed methodology are shown in an application in train traffic control decision support.
{"title":"Knowledge representation and reasoning based on generalised fuzzy Petri nets","authors":"Z. Suraj","doi":"10.1109/ISDA.2012.6416520","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416520","url":null,"abstract":"The aim of this paper is to present a new methodology for knowledge representation and reasoning based on generalised fuzzy Petri nets. Recently, this net model has been proposed as a new class of fuzzy Petri nets. The new class extends the existing fuzzy Petri nets by introducing two operators: t-norms and s-norms, which are supposed to function as substitute for the min and max operators. This model is more flexible than the traditional one as in the former class the user has the chance to define the input/output operators. The choice of suitable operators for a given reasoning process and the speed of reasoning process are very important, especially in real-time decision support systems. The advantages of the proposed methodology are shown in an application in train traffic control decision support.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"19 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114084493","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 : 2012-11-01DOI: 10.1109/ISDA.2012.6416532
J. Horácek, F. Zboril
This article describes our approach to develop a novel system that will automatically select the best node in wireless sensor network, which is suitable for mobile code or mobile agent. We propose to use vague addresation of sensor nodes, that is based on geo-routing algorithms and takes into account other needs of mobile agent such as data validity of values sensed from specific sensor. We will discuss main drawbacks of exact addresation of nodes and reasons why we use vague addressation.
{"title":"Mobile code placement in wireless sensor networks","authors":"J. Horácek, F. Zboril","doi":"10.1109/ISDA.2012.6416532","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416532","url":null,"abstract":"This article describes our approach to develop a novel system that will automatically select the best node in wireless sensor network, which is suitable for mobile code or mobile agent. We propose to use vague addresation of sensor nodes, that is based on geo-routing algorithms and takes into account other needs of mobile agent such as data validity of values sensed from specific sensor. We will discuss main drawbacks of exact addresation of nodes and reasons why we use vague addressation.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124309427","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 : 2012-11-01DOI: 10.1109/ISDA.2012.6416504
R. Marshall
In this paper we discuss a bioinformatics software system which is based on simulating nucleotide sequences at an elemental chemical level using passive electrical circuits comprised of resistors, inductors and capacitors. We focus on the behavior of these circuits for arbitrary user-specified input signals such as speech, music and wave mappings of retinal scans and fingerprints. The circuits' responses are then used to generate distinct visual representations which can be used in a variety of applications including DNA sequence alignments and comparisons, novel biometric identification schemes and computer/network security.
{"title":"Darwin, Debussy an'Dante - a four-part bioinformatics symphony","authors":"R. Marshall","doi":"10.1109/ISDA.2012.6416504","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416504","url":null,"abstract":"In this paper we discuss a bioinformatics software system which is based on simulating nucleotide sequences at an elemental chemical level using passive electrical circuits comprised of resistors, inductors and capacitors. We focus on the behavior of these circuits for arbitrary user-specified input signals such as speech, music and wave mappings of retinal scans and fingerprints. The circuits' responses are then used to generate distinct visual representations which can be used in a variety of applications including DNA sequence alignments and comparisons, novel biometric identification schemes and computer/network security.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121691869","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 : 2012-11-01DOI: 10.1109/ISDA.2012.6416647
Anwar Saeed, A. Al-Hamadi, R. Niese
Improving Human-Computer Interaction (HCI) necessitates building an efficient human emotion recognition approach that involves various modalities such as facial expressions, hand gestures, acoustic data, and biophysiological data. In this paper, we address the perception of the universal human emotions (happy, surprise, anger, disgust, fear, and sadness) from facial expressions. In our companion-based assistant system, facial expression is considered as complementary aspect to the hand gestures. Unlike many other approaches, we do not rely on prior knowledge of the neutral state to infer the emotion because annotating the neutral state usually involves human intervention. We use features extracted from just eight fiducial facial points. Our results are in a good agreement with those of a state-of-the-art approach that exploits features derived from 68 facial points and requires prior knowledge of the neutral state. Then, we evaluate our approach on two databases. Finally, we investigate the influence of the facial points detection error on our emotion recognition approach.
{"title":"Neutral-independent geometric features for facial expression recognition","authors":"Anwar Saeed, A. Al-Hamadi, R. Niese","doi":"10.1109/ISDA.2012.6416647","DOIUrl":"https://doi.org/10.1109/ISDA.2012.6416647","url":null,"abstract":"Improving Human-Computer Interaction (HCI) necessitates building an efficient human emotion recognition approach that involves various modalities such as facial expressions, hand gestures, acoustic data, and biophysiological data. In this paper, we address the perception of the universal human emotions (happy, surprise, anger, disgust, fear, and sadness) from facial expressions. In our companion-based assistant system, facial expression is considered as complementary aspect to the hand gestures. Unlike many other approaches, we do not rely on prior knowledge of the neutral state to infer the emotion because annotating the neutral state usually involves human intervention. We use features extracted from just eight fiducial facial points. Our results are in a good agreement with those of a state-of-the-art approach that exploits features derived from 68 facial points and requires prior knowledge of the neutral state. Then, we evaluate our approach on two databases. Finally, we investigate the influence of the facial points detection error on our emotion recognition approach.","PeriodicalId":370150,"journal":{"name":"2012 12th International Conference on Intelligent Systems Design and Applications (ISDA)","volume":"358 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115893216","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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