Image-based lime size grading using the comparison ratio of the pixel radius and the actual size of lime fruit
Lime is a commercially important fruit in Thailand whose sale price depends on the fruit's size; hence, farmers must grade limes by size before distribution. However, as lime grading machines are very expensive and each province has different size grading limits, grading is often performed manu...
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| Format: | EJournal Article |
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Institute of Advanced Engineering and Science,
2021-10-01.
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| Online Access: | Get fulltext |
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| LEADER | 02599 am a22003133u 4500 | ||
|---|---|---|---|
| 001 | ijeecs24622_15528 | ||
| 042 | |a dc | ||
| 100 | 1 | 0 | |a Chimlek, Pawat |e author |
| 100 | 1 | 0 | |a Ministry of Science and Technology |e contributor |
| 100 | 1 | 0 | |a Naresuan University |e contributor |
| 700 | 1 | 0 | |a Jitanan, Sutasinee |e author |
| 245 | 0 | 0 | |a Image-based lime size grading using the comparison ratio of the pixel radius and the actual size of lime fruit |
| 260 | |b Institute of Advanced Engineering and Science, |c 2021-10-01. | ||
| 500 | |a https://ijeecs.iaescore.com/index.php/IJEECS/article/view/24622 | ||
| 520 | |a Lime is a commercially important fruit in Thailand whose sale price depends on the fruit's size; hence, farmers must grade limes by size before distribution. However, as lime grading machines are very expensive and each province has different size grading limits, grading is often performed manually, which is time-consuming and error-prone. Agricultural production systems for automatic selection and grading use image processing techniques for extracting key features. Therefore, this study proposes techniques to extract features of limes and to develop analytical methods for grading them. This method can reduce time and cost, and increase accuracy and flexibility for selecting different lime sizes according to each province's size criteria. To verify our method, we classified limes according to criteria from four Thailand provinces as sample data in an experiment. The focal image feature was the radius or diameter of the lime and the grading conditions were defined by the maximum comparison ratio of the fruit's radius in pixels to the measured radius of the actual lime in centimeters. The average grading accuracy was 99.59%, which outperformed that of mechanical grading. The processing time was 1.70 seconds per individual fruit. | ||
| 540 | |a Copyright (c) 2021 Institute of Advanced Engineering and Science | ||
| 540 | |a http://creativecommons.org/licenses/by-nc/4.0 | ||
| 546 | |a eng | ||
| 690 | |||
| 690 | |a Image analysis; Image processing; Lime size grading; | ||
| 655 | 7 | |a info:eu-repo/semantics/article |2 local | |
| 655 | 7 | |a info:eu-repo/semantics/publishedVersion |2 local | |
| 655 | 7 | |2 local | |
| 786 | 0 | |n Indonesian Journal of Electrical Engineering and Computer Science; Vol 24, No 1: October 2021; 279-286 | |
| 786 | 0 | |n 2502-4760 | |
| 786 | 0 | |n 2502-4752 | |
| 786 | 0 | |n 10.11591/ijeecs.v24.i1 | |
| 787 | 0 | |n https://ijeecs.iaescore.com/index.php/IJEECS/article/view/24622/15528 | |
| 856 | 4 | 1 | |u https://ijeecs.iaescore.com/index.php/IJEECS/article/view/24622/15528 |z Get fulltext |