Browsing by Author "Jimoh, R. G."
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Item Iris Feature Extraction for Personal Identification using Fast Wavelet Transform (FWT)(International Journal of Applied Information Systems, 2014) Abikoye, O. C.; Sadiku, J. S.; Adewole, K. S.; Jimoh, R. G.Iris is the annular region of the eye bounded by the pupil and the sclera(white of the eye) on either side. The iris has many interlacing features such as stripes, freckles, coronas, radial furrow, crypts, zigzag collarette, rings etc collectively referred to as texture of the iris. This texture is well known to provide a signature that is unique to each subject. All these features are extracted using different algorithms i.e features extraction is the process of extracting information from the iris image. Iris feature extraction is the crucial stage of the whole iris recognition process for personal identification. This is a key process where the two dimensional image is converted to a set of mathematical parameters. The significant features of the iris must be encoded so that comparisons between templates can be made. In this study the feature of the iris is extracted using Fast Wavelet Transform (FWT). The algorithm is fast and has a low complexity rate. The system encodes the features to generate its iris feature codes.Item Office Application in Digital Skill Acquisition, GNS 312,(General Studies Division, University of Ilorin, 2017) Jimoh, R. G.; Ahmed, M. I.,; Mabayoje, M. A.; AbdulRaheem, M.; Salihu, S. AGNS NOTEItem A review of algorithm for fingerprint image acquisition, preprocessing and minutiae extraction(Ilorin Journal of Science, 2015) Adewole, K. S.; Jimoh, R. G.; Abikoye, O. C.Biometric recognition distinguishes between individuals using physical, chemical or behavioral attributes of the person. These attributes are called biometric identifiers or traits, and include fingerprint, palmprint, iris, face, voice, signature, gaint, and DNA among others. Fingerprint recognition is one of the oldest and most reliable biometric used for personal identification. Fingerprint has come a long way from tedious manual fingerprint matching. The ancient procedure of matching fingerprints manually was extremely cumbersome and time-consuming and required skilled personnel. In this paper, a review of algorithms for the various stages involved in fingerprint recognition such as fingerprint image acquisition, segmentation, normalization, ridge orientation estimation, ridge frequency, Gabor filtering, binarization, thinning, minutiae extraction, template generation, and template matching is presented. It was established that minutiae features of a person fingerprint truly make fingerprint of individual to be unique.Item Stepwise biometric procedures for managing student attendance in higher institution of learning(2015) Adewole, K. S.; Jimoh, R. G.; Abikoye, O. C.; Ajiboye, A. R.Data and information security are very important issues in computing environment. Security of data prevents unauthorized users from accessing individual personal information. Biometric is one of the authentication methods used in a wide range of application domains such as airline and banking environment to secure confidential data. This technique is more reliable and capable of distinguishing between an authorized person and an impostor than traditional methods such as passwords. Large numbers of higher academic institutions in the developing countries are still using the process of manual attendance for both lecture and examination for students' authentication and authorization, hence, the need for automated system that can assist in this area. In this paper, stepwise biometric procedures for managing students' attendance for both lectures and examinations are presented. The various stages involved in student attendance management are discussed and simulated. These include enrollment, fingerprint matching and attendance management. The results show that the proposed system is able to identify those students who are qualified to sit for an examination.Item Stock trend prediction using regression analysis–a data mining approach(ARPN Journal of Systems and Software, 2011) Abdulsalam, S. O.; Adewole, K. S.; Jimoh, R. G.Organizations have been collecting data for decades, building massive data warehouses in which to store the data. Even though this data is available, very few of these organizations have been able to realize the actual value stored in it. The question these organizations are asking is how to extract meaningful data and uncover patterns and relationship from their databases. This paper presents a study of regression analysis for use in stock price prediction. Data were obtained from the daily official list of the prices of all shares traded on the stock exchange published by the Nigerian Stock Exchange using banking sector of Nigerian economy with three banks namely:- First Bank of Nigeria Plc, Zenith Bank Plc, and Skye Bank Plc to build a database. A data mining software tool was used to uncover patterns and relationships and also to extract values of variables from the database to predict the future values of other variables through the use of time series data that employed moving average method. The tools were found capable technique to describe the trends of stock market prices and predict the future stock market prices of three banks sampled.