关键词: 质量估计, 神经网络, 多特征, 水产养殖, 图像处理

Abstract: Fish with different weight have different feeding ability. In aquaculture, accurate estimation of fish weight is beneficial for feeding fish in proper amount, avoiding waste of feed and water pollution. Firstly, the image and weight data of crucian carp were collected with a coin as a reference. Secondly, the image was preprocessed and the features of crucian carp and coin were extracted. Finally, BP neural network, Elman neural network and neural network constructed by Numpy library were used to realize the multi-feature weight estimation of crucian carp. The results showed that the determination coefficients of BP and Elman neural network were 0.925 6 and 0.906 4, the mean square errors were 0.003 68 and 0.004 55. The determination coefficient of neural network estimation constructed by Numpy library was 0.823 7, and the mean square error was 0.008 1. Therefore, the BPNN-area-perimeter and Elman-area-perimeter methods could quickly and accurately estimate the weight of fish, realize the precise feeding of fish in aquaculture, classify the fish according to the weight after the fish was caught, and promote the progress of fishery modernization.

Key words: weight estimation, neural network, multi-feature, aquaculture, image process