DEPARTMENT OF ELECTRICAL AND ELECTRONIC ENGINEERING
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Item A prototype of a fingerprint based ignition systems in vehicles(EuroJournal Publishing, Inc., 2011) Omidiora, E. O.; Fakolujo, O. A.; Arulogun, O. T.; Aborisade, D. O.Biometric systems have overtime served as robust security mechanisms in various domains. Fingerprints are the oldest and most widely used form of biometric identification. A critical step in exploring its advantages is to adopt it for use as a form of security in already existing systems, such as vehicles. This research work focuses on the use of fingerprints for vehicle ignition, as opposed to the conventional method of using keys. The prototype system could be divided into the following modules: fingerprint analysis software module that accepts fingerprints images; hardware interface module and the ignition system module. The fingerprint recognition software enables fingerprints of valid users of the vehicle to be enrolled in a database. Before any user can ignite the vehicle, his/her fingerprint image is matched against the fingerprints in the database while users with no match in the database are prevented from igniting the vehicle. Control for the ignition system of the vehicle is achieved by sending appropriate signals to the parallel port of the computer and subsequently to the interface control circuit. The developed prototype serves as an impetus to drive future research, geared towards developing a more robust and embedded real-time fingerprint based ignition systems in vehicles.Item A framework for electronic nose based condition monitoring and diagnosis of automobile engine faults.(Nigeria Computer Society, 2009) Arulogun, O. T; Fakolujo, O. A.; Waheed, M. A.; Omidiora, E. O.; Olaniyi, O. M.A framework for condition monitoring approach that uses the sense of smell was investigated to diagnose the faults of plug-not-firing, loss of compression and carburettor faults from the exhaust fumes of gasoline fuelled automobile engine. An electronic nose based condition monitoring hardware and software was developed using the framework to obtain smell prints that correspond to normal operating conditions and various induced abnormal operating conditions. Fuzzy C-means and K means clustering were used as exploratory data visualization tools to ascertain if the obtained smell prints from the developed system could characterize the faults considered. The results of exploratory cluster analysis showed that the obtained smell print could typify the faults considered.Item Optimised fisher discriminant analysis for recongnition of faces having black features.(Medwell Journals, 2008) Omidiora, E. O.; Fakolujo, O. A.; Ayeni, R. O.; Adeyanju, I. A.A face recognition system is one of the most desirable biometric identification such as computerized access control, document control and database retrieval. Although, several researches have been done on face recognition, most (if not all) have made use of non-black faces or very few numbers of black faces in their experiments. This study presents results of experiments based on black African faces (with and without tribal marks) using the optimized Fisher Discriminant Analysis. In the experiment, different sizes of gray scale images were used for recognition performance accuracy of between 88 and 99% were obtained. Also, taking into consideration was the rate of identifying an image using the same number of images to test the face recognition system. While, a completely robust real-time face recognition system is still under heavy investigation and development, the implemented system serves as an extendable foundation for future research.Item Quantitative evaluation of principal component analysis and fisher discriminant analysis techniques in face images.(Nigeria Computer Society, 2008) Omidiora, E. O.; Fakolujo, O. A.; Ayeni, R. O.; Olabiyisi, S. O.; Arulogun, O. T."Face recognition is an attractive field in enhancing both the security and the image retrieval activities in the multimedia world. Its natural basis in verification or identification purposes is a major factor of its wide acceptance in this evolving world of information technology. In this paper, experiments based on black African faces using Principal Component Analysis (OPCA) and Fisher Discriminant Analysis (OFDA) techniques were carried out. The design of the face recognition system was separated into three major sections - image acquisition and standardisation, dimensionality reduction, training and testing for recognition. Under static mode, experiments were performed on single scaled images without rotation, OPCA and OFDA both give recognition accuracies of between 89% and 97%;and) 88% and 98% respectively. These have been achieved at different levels of cropping. Despite the constraint created by the resources available, different results got showed that standard face recognition system could be developed using both algorithms. "Item A survey of face recognition techniques(Faculty of Technology, University of Ibadan, 2007) Omidiora, E. O.; Fakolujo, O. A.; Ayeni, R. O.; Ajila, T. M.A review of face recognition techniques has been carried out.Face recongition has been an attractive field in the society of both biological and computer vision of research. It exhibits the characteristics of being natural and low-intrusive. In this paper, an updated survey of techniques for face recognition is made. Methods of face regonition , such as geometric, statistical and neural networks approaches are presented and analyzed. The comparative performance of the variaous approaches is discussed.Item A prototype of a robust and secured access control system using principal component analysis(2007) Omidiora, E. O.; Fakolujo, O. A.; Olabiyisi, S. O.; Ayeni, R. O.The need for a robust and secured access control system using a suitable algorithm is highly inevitable to forestall daily online harkers that are responsible in defrauding people of invaluable information and transactions worth billions of dollars in the process. In this paper, faces were employed as the only control means of right of entrance and usage of information on the super-highway. Principal Component Analysis (PCA) was used to perform dimensionality reduction on the feature vectors of the digitized face images. Also, Euclidean distance was the required similarity measure employed to match the tested face with the trained faces inside the database for actual recognition. The result obtained showed that its avarage percentage of rightly classified face was 90.43% and FAR and FRR were 0.1077 &0.0609. An evaluation of the results demostrated PCA to be a very good algorithm for a robust and secured access control and recognition system.Item Fundamentals of Electromechanical Systems(2010-02) Arulogun, O. T.; Fakolujo, O. A.; Omidiora, E. O.; Okediran, O. O.Item Assembly language programming using MC68000(2005-05) Arulogun, O. T.; Fakolujo, O. A.; Omidiora, E. O.; Ajayi, A. O.Item Introduction to measurement and instrumentation(2005-05) Arulogun, O. T.; Fakolujo, O. A.; Omidiora, E. O.; Ajayi, A. O.