|Table of Contents|

Nondestructive Detection of Apple Watercore Based on Hyperspectral Imaging(PDF)

《北方园艺》[ISSN:1001-0009/CN:23-1247/S]

Issue:
2015年08
Page:
124-130
Research Field:
Publishing date:

Info

Title:
Nondestructive Detection of Apple Watercore Based on Hyperspectral Imaging
Author(s):
WANG Si-ling1; CAI Cheng2; MA Hui-ling1; LONG Yi-lin2
(1.College of Life Science，Northwest Agriculture and Forest University，Yangling，Shannxi 712100；2.College of Information Engineering，Northwest Agriculture and Forest University，Yangling，Shannxi 712100)
Keywords:
apple; watercore; hyperspectral image; feature selection; SVM; kernel function
PACS:
S 661.101
DOI:
10.11937/bfyy.201508033
Abstract:
In order to evaluate the ability of near infrared hyperspectral imaging to detect watercore in apple fruits，hyperspectral images of 240 apples cv.‘Qinguan’ including sound fruit and watercore fruit were collected by near infrared hyperspectral camera (900-1 700 nm).The apple regions of hyperspectral images were extracted as region of interest (ROI) in which its average spectrum was calculated.To recognize watercore fruits，4 kinds of feature selection methods and 3 kinds of kernel function of support vector machine (SVM) classifier were adopted.The results showed that 2 kinds of feature selection which based on chi-square test and support vector machine recursive feature elimination (SVM-RFE) were superior to the methods of F classic test and decision tree.The accurate rate of watercore distinguish of 4 kinds of feature selection with 3 kinds of kernel function of SVM classifier at 1-200 wavebands was 48.6%-70.2%，48.6%-72.0%，33.3%-71.8% and 47.2%-70.8%,respectively；moreover，the accurate rate of watercore distinguish based on SVM-RFE，which was the best method，reached the highest level of 72.0%.

References:


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Last Update: 2015-08-07