Profile Summary

An inspiring self-motivate and dynamic university lecturer with experience (9 years) in lecturing engineering courses, and total of (25 years) in education and industrial work experience. I have a strong and passion skill for learning and developing, I enjoy being part of and encouraging inclusive team and promoting good positive skills technique. Possesses exemplary planning skills and accustomed to operating under considerable pressure, remaining calm, effective, and prioritizing wisely. I have always had passion for creativity and developments.

Education Background

PhD in Computer Engineering. Universiti Malaysia Perlis (UniMAP)

Thesis Title

An Enhanced Markov Random Field (MRF) based Approach for Image Segregation.

The main objective of this research is to present an alternative technique to enhance the depth segregation of a 2D monocular image using Markov Random Field (MRF). Depth segregation considered challenging task due to an extensive segment of textural contrasts among objects. Objects appearance in varies shape and location in the scene, depth segregation is likewise made difficult due to extra components, occluded objects, which can be either visible or totally invisible from the scene, the existing of unpredictable image accommodate in an unconstrained environment most likely to increase the difficulty of the process.

Depth image segregation technique that has been proposed technique initially executes image segmentation; to identify region in the image, morphological operation; to eliminate any error pixel, then edge detection; to identify the boundaries of the regions, and use this information to perform depth segregation process to identify and label the objects in depth labelled order.

The experimental result show that the technique has successfully segregated the regions in depth order from a 2D monocular image, the segmented image has been combined with the edge detection image to perform the depth segregation process and the result was efficient in terms of object labeling order in 3D environment. The result show the ability of the technique to be integrated with a universal system, the proposed technique based approach is more flexible since it can treat cases such occlusion and not simply connected foreground region. Due to the robust approach by segregation technique, since it can deal with images including textured regions with high intensity variations.

Areas of Expertise

Signal processing, Image processing (2D and 3D), Android developer, Electronics, Micro-controller, PIC, PLC, Simulation, Control System, Computer programming, Artificial intelligent (AI), Algorithms, Robotics, Biomedical Engineering (IRIS, CTG, ECG and EEG signals).