基于颜色和重量特征的苹果在线分级系统设计

针对目前水果分级自动化程度较低且分级系统均为离线工作台方式的问题，设计了一种基于多信息融合的苹果采摘机器人在线自动分级系统。在提取苹果重量及颜色两个特征参数后，运用权重分析法对这两个特征参数进行数据融合，以实现双特征综合分级。为提高分级正确率，通过实验优化了权重系数。实验结果表明：所设计的分级系统可实现按重量和颜色双特征进行苹果分级，分级正确率达87%以上。

Design of on-line apple grading system based on color and weight

Aimed at the problem that the automatic level of fruit grading and all fruit grading systems work in the way of off-line at present, one kind of apple on-line automatic grading system is designed for apple picking robots based on multi-information fusion. Weight and color characteristic parameters of the apple are extracted, the data are fused through weight analysis to achieve comprehensive grading based on multi-feature. To improve the accuracy of grading, the weight coefficients are optimized by experiments. Experimental results show that the designed system can achieve grading based on double-feature（weight and color） with the correct rate of over 87%.