基于K-means聚类算法分类的水果等级识别与应用

Recognition and Application of Fruit Classification Based on K-means Clustering Algorithms

首先介绍了K-means算法的思想和原理,然后对水果分类模型图像的获取和预处理进行分析研究,最后实现了K-means聚类和BP神经网络相结合的水果等级分类识别模型。试验结果表明:采用K-means聚类和BP神经网络相结合的方法,大大提高了水果分类识别的准确率,并使得识别时间大大缩短,具有一定的现实意义。

It firstly introduced the idea and principle of K-means algorithm.Then,it analyzed and studied the image acquisition and preprocessing of fruit classification model.Finally,it realized a fruit classification and recognition model based on K-means clustering and BP neural network.The experimental results show that the combination of K-means clustering and BP neural network greatly improves the accuracy of fruit classification and recognition,and greatly reduces the recognition time,which has a certain practical significance.