Human-Computer Interface (HCI) enables people to control computer applications using bio-electric signals recorded from the body. HCI can be a potential tool for people with severe motor disabilities to communicate to external world through bio-electric signals. In an Electrooculogram (EOG) based HCI, signals during various eye (cornea) movements are employed to generate control signals. This paper presents the design of an EOG-based typing system which uses a virtual keyboard for typing letters on the monitor using 8 types of distinct EOG patterns. Identification of EOG pattern is based on the amplitude and timing of positive and negative components within the signal. Experimental results show that proposed EOG-based typing system achieves a higher typing speed of 15 letters/min and an improved accuracy of 95.2% compared to the state-of art method that has a typing speed of 12.1 letters/min and accuracy of 90.4%.