Abstract:
This thesis presents a new approach to automate the classification and estimation of
coral reef based on computer vision techniques by performing classification and
recognition on digitized video obtained from surrounding reef ecosystem. By knowing the state of the coral reefs, marine scientist can predict fish yield or determine how the
reef system is coping with the environment in a less tedious and less time consuming
way. In this project, the objective is to classify and recognize a predetermined reef
benthos groups. These groups are alive coral, dead coral, sand and rubble. As for the alive coral group, possible higher level of taxonomic classification is performed to
discriminate the classes of branching, digitate and tabulate solely based on digital video recording.
