基于颜色信息和形状特征的棉桃识别方法

Using Color Data and Shape Properties for Cotton Fruit Recognition

为了给机械手自动采摘棉桃提供运动参数,提出了一种棉桃识别方法,可以从背景环境中准确识别棉桃,获取棉桃准确的位置信息。通过对棉花不同部分颜色数据的分析,建立了基于色差信息的识别模型,为进一步提高识别准确性,利用形状特征建立动态Freeman编码方法去除噪声。实验结果表明这种方法具有良好的棉桃识别效果,识别率达到85%。

In order to provide parameters for the motion of cotton fruit auto-picking manipulator, a new cotton recognition method was proposed. The method can identify cotton fruits from surroundings correctly, acquire their precise location information, and accordingly pick up automatically. By analysis on the color data of different parts of cotton in RGB space, a conclusion is obtained that the values of red and blue color of cotton fruits are distributed on the line of 45°, while those of cotton leaves and stems deviate from this line. Base on this, the method using color subtraction information is designed. Furthermore, in order to improve the accuracy of cotton recognition, according to shape properties, a new dynamic edge tracing method via Freeman chain coding is used to remove the background noise. Experimental results show that the proposed method has good performance of identification, and the accuracy is more than 85%.