科研之友
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摘要
A periodic sorting of fish is important to achieve optimal growth rates and efficient fish farm operations. Conventional methods, however, are labour intensive, cause stress to the fish and increase the risk of injuries. To overcome these problems a device has been developed for automatic and stress free sorting of fish by means of digital image processing. The main part of the device consists of an underwater monitoring channel, which is able to direct fish through different exits according to their weight. The decisions on weight class sorting are induced by basic computer algorithms. Experimental results show that a linear regression model based on a correlation between silhouette area and absolute body mass is able to estimate body mass with a relative average error of 5.5% (n = 50). The rates at which the fish swim through the device are found to be seven and 30 fish per hour, suggesting a dependence on the fish density in the sorting tank. It is hypothesized that the relative position and the behaviour of the fish within the sorting channel, among other factors, influence the model accuracy and hence the sorting decision. For future work, an improved sorting device is planned by adding commercially relevant functions for individual fish identification and monitoring that are based upon finger-print-like morphological features of individual fish.
- 出版日期2011-4
