基于BP神经网络的水果识别系统  

Fruit Identification System Based on Matlab

作　　者：罗志翔 胡蓉[1] 赵全友[1] 邓雄昌 LUO Zhi-xiang;HU Rong;ZHAO Quan-you;DENG Xiong-chang(Hunan University of Science and Engineering,Yongzhou 425199,China)

机构地区：[1]湖南科技学院,湖南永州425199

出　　处：《电脑知识与技术》2021年第4期187-189,共3页Computer Knowledge and Technology

基　　金：湖南省2018年度重点研发计划资助项目(2018NK2063);湖南科技学院应用特色学科建设项目资助。

摘　　要：近些年,计算机视觉发展迅速,在水果识别方向进行了广泛的应用和研究。本文设计基于BP神经网络的水果识别系统,选取生活中常见的三种水果:苹果、橘子、香蕉作为对象。首先,通过网络资源等搜集水果图像建立样本库;然后通过MATLAB对图像进行预处理,为后续的特征提取做好准备。水果特征的提取选择纹理、形状、颜色三种特征进行提取;同时在每种特征中选用不同的特征值作为特征向量。通过提取三种特征后输入到BP神经网络中进行训练、识别。经测试,识别的成功率可以达到93.18%,证明了可行性以及未来的可实用性。Computer vision has developed rapidly in recent years,and has been widely used and researched in the direction of fruit recognition.This paper designs a fruit recognition system based on BP neural network.Choose three common fruits in life:apples,oranges,and bananas as objects.First,collect fruit images through network resources to establish a sample library.Then the image is preprocessed by MATLAB software to prepare for subsequent feature extraction.For the extraction of fruit features,three fea⁃tures of texture,shape,and color are selected for extraction;at the same time,different feature values are selected as feature vectors in each feature.After three kinds of features are extracted,they are input into BP neural network for training and recognition.After the recognition test,the recognition success rate can reach 93.18%,which proves the feasibility and practicality in the future.

关 键 词：水果识别 MATLAB 特征提取 BP神经网络 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]