Iris recognition uses automated techniques to extract iris features which are stored in a database as a feature template to be later used for individual identification and authentication. Strict image quality control is a basic requirement for most iris identification systems. Low cost devices used under uncontrolled environments acquire poor iris images with inconsistent illumination and specular reflections. These factors inflict challenges towards the accurate identification and extraction of reliable iris features. This work proposes a fusion of Phase congruency and Harris algorithm to detect corner features found within the arrangement of iris patterns. This fusion produces a feature vector with the exact location of corner features that are not only congruent in phase but are also invariant to illumination and rotation. Results of the proposed approach are tested on two non-ideal databases and obtain an accurate match rate of 99.9% while producing a feature template of 512 bits that requires low storage space.
{"title":"Fusion of Phase Congruency and Harris Algorithm for Extraction of Iris Corner Points","authors":"G. Mabuza-Hocquet, F. Nelwamondo","doi":"10.1109/AIMS.2015.57","DOIUrl":"https://doi.org/10.1109/AIMS.2015.57","url":null,"abstract":"Iris recognition uses automated techniques to extract iris features which are stored in a database as a feature template to be later used for individual identification and authentication. Strict image quality control is a basic requirement for most iris identification systems. Low cost devices used under uncontrolled environments acquire poor iris images with inconsistent illumination and specular reflections. These factors inflict challenges towards the accurate identification and extraction of reliable iris features. This work proposes a fusion of Phase congruency and Harris algorithm to detect corner features found within the arrangement of iris patterns. This fusion produces a feature vector with the exact location of corner features that are not only congruent in phase but are also invariant to illumination and rotation. Results of the proposed approach are tested on two non-ideal databases and obtain an accurate match rate of 99.9% while producing a feature template of 512 bits that requires low storage space.","PeriodicalId":121874,"journal":{"name":"2015 3rd International Conference on Artificial Intelligence, Modelling and Simulation (AIMS)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122036728","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 article present a minutiae matching algorithm using hardware based artificial neural network intended to be implemented in embedded system environment. Hardware based artificial neural network CM1K consist of 1024 neuron in Cognistix device is used in this research. Fingerprint template as a vectors of minutiae points is used as an input to artificial neural network device. Matching process is based on the calculation of the distance from two vectors from two set of minutiae points comming from two fingerprints. Using hardware based of artificial neural network provide faster processing in matching process and the used of Cognistix making faster and easy in development of prototype.
{"title":"Minutiae Matching Algorithm Using Artificial Neural Network for Fingerprint Recognition","authors":"Hariyanto, S. Sudiro, S. Lukman","doi":"10.1109/AIMS.2015.16","DOIUrl":"https://doi.org/10.1109/AIMS.2015.16","url":null,"abstract":"This article present a minutiae matching algorithm using hardware based artificial neural network intended to be implemented in embedded system environment. Hardware based artificial neural network CM1K consist of 1024 neuron in Cognistix device is used in this research. Fingerprint template as a vectors of minutiae points is used as an input to artificial neural network device. Matching process is based on the calculation of the distance from two vectors from two set of minutiae points comming from two fingerprints. Using hardware based of artificial neural network provide faster processing in matching process and the used of Cognistix making faster and easy in development of prototype.","PeriodicalId":121874,"journal":{"name":"2015 3rd International Conference on Artificial Intelligence, Modelling and Simulation (AIMS)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128692860","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 study proposes a new scheme for MIMO-based ad hoc networks. This is accomplished, while using the Interference Driving Technique (IDT) over Nakagami-m fading channels with perfect channel state information at both the transmitter and receiver. The use of this technique is proposed to decrease the impact of all the unwanted interferences, routinely caused by the overlap of the defined radio transmission ranges related to the used nodes. Indeed, IDT is utilized as a coordinated beam former in a cooperative scheme, according to mean squared error criterion. The methodology and also analytical results are conducted to prove the aptitude of the paper.
{"title":"A New Coordinated Beamformer for MIMO-Based Ad Hoc Networks","authors":"Makan Zamanipour, M. Mohammadi","doi":"10.1109/AIMS.2015.68","DOIUrl":"https://doi.org/10.1109/AIMS.2015.68","url":null,"abstract":"The study proposes a new scheme for MIMO-based ad hoc networks. This is accomplished, while using the Interference Driving Technique (IDT) over Nakagami-m fading channels with perfect channel state information at both the transmitter and receiver. The use of this technique is proposed to decrease the impact of all the unwanted interferences, routinely caused by the overlap of the defined radio transmission ranges related to the used nodes. Indeed, IDT is utilized as a coordinated beam former in a cooperative scheme, according to mean squared error criterion. The methodology and also analytical results are conducted to prove the aptitude of the paper.","PeriodicalId":121874,"journal":{"name":"2015 3rd International Conference on Artificial Intelligence, Modelling and Simulation (AIMS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130500095","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}
Software quality issues require special attention especially in view of the demands of quality software product to meet customer satisfaction. Software development projects in most organisations need proper defect management process in order to produce high quality software product and reduce the number of defects. The research question of this study is how to produce high quality software and reducing the number of defects. Therefore, the objective of this paper is to provide a framework for managing software defects by following defined life cycle processes. The methodology starts by reviewing defects, defect models, best practices and standards. A framework for defect management life cycle is proposed. The major contribution of this study is to define a defect management roadmap in software development. The adoption of an effective defect management process helps to achieve the ultimate goal of producing high quality software products and contributes towards continuous software process improvement.
{"title":"Defect Management Life Cycle Process for Software Quality Improvement","authors":"Aedah Abd. Rahman, N. Hasim","doi":"10.1109/AIMS.2015.47","DOIUrl":"https://doi.org/10.1109/AIMS.2015.47","url":null,"abstract":"Software quality issues require special attention especially in view of the demands of quality software product to meet customer satisfaction. Software development projects in most organisations need proper defect management process in order to produce high quality software product and reduce the number of defects. The research question of this study is how to produce high quality software and reducing the number of defects. Therefore, the objective of this paper is to provide a framework for managing software defects by following defined life cycle processes. The methodology starts by reviewing defects, defect models, best practices and standards. A framework for defect management life cycle is proposed. The major contribution of this study is to define a defect management roadmap in software development. The adoption of an effective defect management process helps to achieve the ultimate goal of producing high quality software products and contributes towards continuous software process improvement.","PeriodicalId":121874,"journal":{"name":"2015 3rd International Conference on Artificial Intelligence, Modelling and Simulation (AIMS)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129037963","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}
Active collaboration among green-energy and the load demand lead to serious issue related to power quality and stability. This requires newer strategies to be incorporated to keep the power stability among green energy resources and micro-grid/Utility Grid. This paper presents a novel technique for power management in Grid-connected photovoltaic system with an energy storage system under a set of constraints, including weather conditions, load-shedding hours, peak pricing hours, by using rule-base fuzzy smart controller to schedule power coming from multiple sources (Photovoltaic, Grid, Battery) under the above set of constraints. The technique fuzzify all the inputs and establishes fuzzify rule set from fuzzy outputs before deffuzification process. Simulations are run for 24 hour period and rule base power scheduler is developed. The Proposed fuzzy control strategy is able to sense the continuous fluctuations in photovoltaic power generation, Load Demands, Grid (load Shedding patterns), and Battery State of Charge in order to make correct and quick decisions. The Suggested Fuzzy Rule based scheduler can operate well with vague inputs, thus doesn't not require any exact numerical model and can handle nonlinearity by combining the human heuristics into computer assisted decisions. This technique also provides a framework for extension to handle multiple special cases for an optimized working of the system.
{"title":"Power Energy Management for a Grid-Connected PV System Using Rule-Base Fuzzy Logic","authors":"Nousheen Hashmi, S. Khan","doi":"10.1109/AIMS.2015.15","DOIUrl":"https://doi.org/10.1109/AIMS.2015.15","url":null,"abstract":"Active collaboration among green-energy and the load demand lead to serious issue related to power quality and stability. This requires newer strategies to be incorporated to keep the power stability among green energy resources and micro-grid/Utility Grid. This paper presents a novel technique for power management in Grid-connected photovoltaic system with an energy storage system under a set of constraints, including weather conditions, load-shedding hours, peak pricing hours, by using rule-base fuzzy smart controller to schedule power coming from multiple sources (Photovoltaic, Grid, Battery) under the above set of constraints. The technique fuzzify all the inputs and establishes fuzzify rule set from fuzzy outputs before deffuzification process. Simulations are run for 24 hour period and rule base power scheduler is developed. The Proposed fuzzy control strategy is able to sense the continuous fluctuations in photovoltaic power generation, Load Demands, Grid (load Shedding patterns), and Battery State of Charge in order to make correct and quick decisions. The Suggested Fuzzy Rule based scheduler can operate well with vague inputs, thus doesn't not require any exact numerical model and can handle nonlinearity by combining the human heuristics into computer assisted decisions. This technique also provides a framework for extension to handle multiple special cases for an optimized working of the system.","PeriodicalId":121874,"journal":{"name":"2015 3rd International Conference on Artificial Intelligence, Modelling and Simulation (AIMS)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-10-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123017526","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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