Open AccessVision-based Size Estimation and Centroid Positioning of Partially Occluded Fruits
Author(s) -
Mya Thin Kyu Kyu,
Nay Aung
Publication year - 2020
Publication title -
asean journal on science and technology for development/asean journal on science and technology for development
Language(s) - English
Resource type - Journals
eISSN - 2224-9028
pISSN - 0217-5460
DOI - 10.29037/ajstd.636
Subject(s) - centroid , conic section , mathematics , ellipse , artificial intelligence , image processing , computer vision , statistics , computer science , geometry , image (mathematics)
The objective of this study was to propose a simple and efficient image processing algorithm for estimating the size and centroid of partially occluded round fruits. In the proposed method, the size and centroid of partially occluded fruit were estimated based on the mathematical properties of the arc-radius. The experimental tests were conducted in a laboratory with orange, Sunkist, apple, and tomato fruits by setting different occlusion conditions. The occlusion percentage was varied between 0% and 90%. The accuracy and processing time of the proposed method were compared with that of the widely-used conic-section circle fitting method. The results showed that the proposed method resulted in an overall accuracy of 95.1% and processing time of 0.66 s, as opposed to 60.2% and 0.68 s, respectively, using the conic-section equation. Compared with the conic-section equation, the proposed method was able to give a more robust prediction, even for low resolution images.