Tracking Multiple Fishes Using Colour Changes Identification and Enhanced Object Tracking Algorithm

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.

• Periodical: Applied Mechanics and Materials (Volumes 284-287)
• Pages: 1528-1532
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.284-287.1528
• Online since: January 2013
• Authors: Wong Poh Lee, Mohd Azam Osman, Abdullah Zawawi Talib, Khairun Yahya
• Keywords: Colour Changes Identification, Condensation Algorithm, Fish Tracking, Motion Detection

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