一种新型苹果果实特征提取算法

A new algorithm for fruit feature extraction of apple

针对当前苹果特征提取常用的Hough算法存在运算复杂、实时性差等缺陷,提出了一种新型苹果果实特征提取算法。该算法利用一个滑动的高斯模板和苹果图像进行卷积运算提取苹果的圆形。试验及仿真结果表明,该方法可以实现单一、相邻和重叠3种情况下,苹果果实检测的高准确率,且在相邻并重叠的复杂情况下,其识别准确率也能达到94.1%,而在单个苹果的情况下,苹果果实的检测准确率可达96.6%,完全满足苹果实时、高效分级的需要。

At present,the main algorithm used in feature extraction of apple is the traditional Hough algorithm.The algorithm has the disadvantages of complicated operation and poor real-time performance.In view of this situation,a new algorithm of apple fruit feature extraction is proposed in this paper.A sliding Gaussian template and apple image are convoluted to extract apple circles in this algorithm.Experiments and simulation results show that this method can achieve high accuracy of apple fruit detection under single,adjacent and overlapping conditions.In the case of a single apple,the detection accuracy of apple fruit can reach 96.6%.Even in the case of contiguous and overlapping,its recognition accuracy can reach 94.1%.It fully meets the needs of apple＇s real-time,efficient grading.