15-12-2025
جامعة الملك عبدالعزيز
KING ABDULAZIZ UNIVERSITY
Faculty of Computing and Information Technology in Rabigh
Document Details
Document Type
:
Article In Journal
Document Title
:
Natural Produce Classification Using Computer Vision Based on Statistical Color Features and Derivative of Radius Function
Natural Produce Classification Using Computer Vision Based on Statistical Color Features and Derivative of Radius Function
Subject
:
Computer Science
Document Language
:
English
Abstract
:
In agriculture industry, natural produce classification is used in sorting, grading, measuring, and pricing. Currently, a lot of methods have been developed using computer vision to replace human expert in natural produce classification. However, some of the method used long features descriptor and complex classifier to obtain high classification rate. This paper proposes natural produce classification method using computer vision based on simple statistical color features and derivative of radius function. The k-nearest neighbors (k-NN) and artificial neural network (ANN) were used to classify the produce based on the extracted features. Preliminary experiment results show that the proposed method achieved best result with average classification accuracy of 99.875% using ANN classifier with nine nodes in hidden layer.
ISSN
:
1662-7482
Journal Name
:
Applied Mechanics and Materials
Volume
:
771
Issue Number
:
2015
Publishing Year
:
1436 AH
2015 AD
Article Type
:
Article
Added Date
:
Monday, March 7, 2016
Researchers
Researcher Name (Arabic)
Researcher Name (English)
Researcher Type
Dr Grade
Email
Anton Satria Prabuwono
Satria Prabuwono, Anton
Researcher
Doctorate
antonsatria@eu4m.eu
Files
File Name
Type
Description
38351.pdf
pdf
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