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Real Time Eyeball Tracking Via Derivative Dynamic Time Warping For Human-Machine Interface, Norrima Mokhtar
Real Time Eyeball Tracking Via Derivative Dynamic Time Warping For Human-Machine Interface, Norrima Mokhtar
Mokhtar Norrima
In this paper, a real time, user independent eyeball tracking approach is presented. The system is implemented by using a low cost webcam. The robustness of the system is measured by several criteria such as users of different age where some of the users are wearing glasses under varying lighting condition, pose, eye orientation and distance from camera. The size and location of the region of interest which contains both eyes are made adaptive. Derivative Dynamic Time Warping is chosen as the classifier for this experiment since it can match patterns from data sequences with different lengths. Finally, the results, …
Dual Modality Search And Retrieval Technique Analysis For Leukemic Information System, Norrima Mokhtar
Dual Modality Search And Retrieval Technique Analysis For Leukemic Information System, Norrima Mokhtar
Mokhtar Norrima
Medical Information System (MIS) deals with standardized method of collection, storage, retrieval and evaluation of patient data. Computational Intelligence (CI) technique has many abilities in data processing and structuring, pattern matching, forming knowledge base, reasoning and decision making. MIS for leukemia cells was developed at University of Malaya for the Hematology Department of Hospital Ampang, Malaysia. CI techniques were used for syntactical and contextual image retrieval of leukemic images. A logical approach was used to systematically develop content based image retrieval system that supports decision making in clinical hematopathology. The developed system is based on open source. Pages were designed …
Real Time Noise-Speech Discrimination In Time Domain For Speech Recognition Application, Norrima Mokhtar
Real Time Noise-Speech Discrimination In Time Domain For Speech Recognition Application, Norrima Mokhtar
Mokhtar Norrima
A simple noise-speech discrimination method in time domain is presented. The random signal noise characteristics were studied in time domain. Using the characteristics information, in real time processing, a simple algorithm to detect starting and ending point of speech samples in time domain is being demonstrated. Out of 100 attempts, about 94% of successful attempts of noise-speech discrimination have been obtained with white noise background by choosing the critical thresholds values.