Performance Evaluation of Deep Learning based Mandarin Fruit Sorting System with Industrial Camera

人工智能 计算机科学 学习迁移 模式识别(心理学) 分类 图像分割 卷积神经网络 聚类分析 深度学习 预处理器 上下文图像分类 分割 计算机视觉 图像(数学) 算法
作者
Muralidharan Duraisamy,Rajavendhan Govindaraj,N. Sri Ram Mohan,Anandhanarayanan Kamalakannan,Satish Bindal,Anita Titus
标识
DOI:10.1109/icosec54921.2022.9951937
摘要

Manual inspection of fruit surface defects is time consuming, involves labour cost, prone to human error and possess inconsistent classification standards in fruit sorting application. To solve this issue, an automatic fruit sorting algorithm using deep learning technique was proposed to identify surface defects namely splitting, pitting, and stem-end rot found in mandarin fruits. The fruit sorting algorithm consists of K-Medoids segmentation and Convolutional Neural Network (CNN) classification model. The grayscale images of mandarin fruit surface were captured from an image acquisition system built with Near Infrared (NIR) camera. A preprocessing median filter was applied to remove random noise. After preprocessing, segmentation was carried out using K-Medoids clustering to crop the fruit surface image from the background region. Different CNN models namely VGG-16, InceptionV3 and MobileNet were trained and tested with and without transfer learning approach using the cropped image dataset. After training, the cropped fruit surface image was given to CNN model for defect classification. The classification results of the above models improved significantly after implementing transfer learning method. The VGG-16 model achieved a maximum overall classification accuracy of 90% without transfer learning and 99.53% with transfer learning approach when compared with the InceptionV3 and MobileNet. Overall accuracy of MobileNet improved from 57% to 98% after transfer learning and also it takes minimum time for inference. Considering both the overall accuracy and inference time parameters with the transfer learning approach, the MobileNet is found to be the best model for mandarin fruit sorting application.
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