In recent years, we can see an increasing use of image processing systems in various business sectors, such as agriculture, where quality testing and monitoring processes are still performed manually. Because of low equipment prices and advances in the field of image processing, many traditional areas are leaning towards automation solutions.
In this project we attempt to characterize fish behavior in pools during the day and build up a system that will alarm in case of untypical fish behavior, such a behavior may indicate of a change in the fish living conditions or diseases.
Assumptions and Difficulties
The main assumption which the project is based on is that sick fish do not eat and are apathetic to environment changes.
In addition, fish are frequently ill.
Fish pools are dynamic environment and therefore it is hard to separate the fish movement from the pools background.
The water in the pools always moving and has reflections from the light changes during the day. Another difficulty is to recognize the fish food because it is given in small doses.