CAJ | 학술논문

传统梭子蟹养殖定期质量估计的方法是捕捞部分梭子蟹进行称重,会对其造成物理和应激伤害,且检测过程中受到人为因素干扰,因此利用机器视觉技术对梭子蟹的质量进行估计.通过摄像头拍摄不同生长阶段的梭子蟹图像,对图像进行模板校正及图像分割,提取梭子蟹面积特征参数.利用最小二乘法对面积和质量进行拟合,其中二次多项式相关性最好可达到0.9220,测试平均相对误差6.40%,证明该方法可以满足梭子蟹质量估计的要求.
전통사자해양식정기질량고계적방법시포로부분사자해진행칭중,회대기조성물리화응격상해,차검측과정중수도인위인소간우,인차이용궤기시각기술대사자해적질량진행고계.통과섭상두박섭불동생장계단적사자해도상,대도상진행모판교정급도상분할,제취사자해면적특정삼수.이용최소이승법대면적화질량진행의합,기중이차다항식상관성최호가체도0.9220,측시평균상대오차6.40%,증명해방법가이만족사자해질량고계적요구.
The traditional means of weight estimation for swimming crabs is catching some samples to weigh, which may raise some unwanted issues such as safety problems, high labor cost, time-consuming, human subjectivity and low efficiency. In this paper, the machine vision technology is applied to facilitate the weighing process. First, the image and the weight data of a swimming crab at different growth stages are collected. Then the image is digitally processed for correction and segmentation through which the area of swimming crab can thus be identified. Data fitting between area and weight is conducted using the least squares technique. It is found that the best fitting can be obtained using quadratic polynomial with correlation coefficient being 0.9220 and average relative being 6.40%, suggesting the validation of the proposed method for weight estimation of swimming crabs.