When viewing the surrounding environment, the human eyes perform different eye movements that reflect human's interest and attention. A large amount of research efforts have focused on Areas of Interest (AOIs)-based transition analysis of eye movement. However, to the best of our knowledge, there is little work on fixation duration from eye tracking data. In this paper, we investigate entropy based eye movement transition analysis of fixation duration. Specifically, we divide the fixation duration into three categories - express fixations (called short duration, SD), cognitive fixations (called medium duration, MD), and very long fixations (called long duration, LD), and model the eye tracking sequences of fixation duration as a Markov chain, which is further considered from the perspective of a discrete information channel. Subsequently, we exploit the information channel paradigm by computing the entropy measures from the fixation duration information channel to explore the visual behaviour. The proposed method, that allows a straightforward clustering of the results, is demonstrated on two eye tracking data sets, Van Gogh paintings and scientific posters, and shows that the differences between observers are more pronounced that the differences between the observed images. The findings from this work might also provide future insights to quantitative assess human visual cognitive process.