Abstract
Tracking multiple fishes using computational methods have become a research endeavor among researchers. Different concepts have been taken such as installing water sensors and video cameras to identify movement speed, colours, shapes and swimming patterns displayed by the fishes. In this research, an enhanced algorithm consisting of motion detection algorithm and condensation algorithm is proposed. This algorithm is further integrated with colour changes identification technique which considers the changes in colour on fishes. This is to identify overlapping fishes and to detect the distance between the camera and the fishes in the water. In our case study, a cultured fish tank installed with water sensors to monitor water pH, dissolved oxygen and temperature is set up together with two network cameras. Koi fishes are chosen due to their active swimming behaviour, variety of colours and easy-to-adapt habitat in the water. A real-time prototype system which models the fish swimming pattern consisting of the enhanced algorithm and the colour changes identification is developed.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.