Abstract: In order to carry out non-destructive estimation of the weight of Scophthalmus maximus, a weight estimation model was proposed based on depth image. The method firstly performed image preprocessing on the depeth image, extracted the target feature by using the growth data-mapping model, then combined the grid search optimization support vector regression (GS-SVR) algorithm to realize the weight estimation of Scophthalmus maximus. The estimated results were compared with the actual measured results. Experiment showed the optimal fit (R2) was 0.990 1, The root mean square error (RMSE) was 0.029 7. The model had the characteristics of simple and flexible, high estimation accuracy and easy implementation,which has a good application prospect.

Key words: Scophthalmus maximus, depth image, data-mapping model, weight estimation

摘要： 为了对大菱鲆体重进行无损估测，提出了一种基于深度图像的大菱鲆体重估测模型。该方法首先对大菱鲆深度图像进行图像预处理，提取出深度信息与生长数据进行映射建模，拟合出目标特征，并结合网格搜索优化支持向量回归（GS-SVR）算法，实现大菱鲆体重估测。估测结果与实际测量结果进行对比，两者的决定系数（R2）达到0.990 1,均方根误差(RMSE)为0.029 7。该模型具有简单灵活、估测精度高和易于实现等特点，同时具有很好的应用前景。

关键词: 大菱鲆, 深度图像, 映射模型, 体重估测