Defects detection algorithm of harumanis mango for quality assessment using colour features extraction. Journal of Physics: Conference Series, 2107. pp. 1-8. ISSN 1742-6596 (2021)
Abstract
Visual defects detection is one of the main problems in the post-harvest processing caused a major production and economic losses in agricultural industry. Manual fruits detection become easy when it is done in small amount, but the result is not consistent which will generate issue in fruit grading. A new fruit quality assessment system is necessary in order to increase the accuracy of classification, more consistencies, efficient and cost effective that would enable the industry to grow accordingly. In this paper, a method based on colour feature extraction for the quality assessment of Harumanis mango is proposed and experimentally validated. This method, including image background removal, defects segmentation and recognition and finally quality classification using Support Vector Machine (SVM) was developed. The results show that the experimental hardware system is practical and feasible, and that the proposed algorithm of defects detection is effective.
| Item Type: | Article |
|---|---|
| Keywords: | Harumanis mango, Quality assessment, Defects detection, Grading processing |
| Taxonomy: | By Niche > Harum Manis > Grading By Niche > Harum Manis > Processing By Niche > Harum Manis > Quality |
| Local Content Hub: | Niche > Harum Manis |
| Depositing User: | Nur Hayati Abdul Satar |
| Date Deposited: | 21 Sep 2023 06:38 |
| Last Modified: | 21 Sep 2023 06:38 |
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