Mohamed Rizon

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In this paper we propose a new algorithm to detect the irises of both eyes from a face image. The algorithm ÿrst detects the face region in the image and then extracts intensity valleys from the face region. Next, the algorithm extracts iris candidates from the valleys using the feature template of Lin and Wu (IEEE Trans. Finally, using the costs for pairs(More)
This study presents the processes undertaken in the design and development of an intelligent omni-directional mobile robot using four custom-made mecanum wheels. The mecanum wheel developed consists of nine rollers made from delrin. All mecanum wheels are independently powered using four units of precisian gear DC motors and the wheel/motor assemblies were(More)
— This paper proposes an emotion recognition system from EEG (Electroencephalogram) signals. The main objective of this work is to compare the efficacy of classifying human emotions using two discrete wavelet transform (DWT) based feature extraction with three statistical features. An audiovisual induction based protocol has been designed to acquire the EEG(More)
This study proposes a statistical features-based classification system for human emotions by using Electroencephalogram (EEG) bio-sensors. A total of six statistical features are computed from the EEG data and Artificial Neural Network is applied for the classification of emotions. The system is trained and tested with the statistical features extracted(More)