دورية أكاديمية
Multi-Feature Patch-Based Segmentation Technique in the Gray-Centered RGB Color Space for Improved Apple Target Recognition
| العنوان: | Multi-Feature Patch-Based Segmentation Technique in the Gray-Centered RGB Color Space for Improved Apple Target Recognition |
|---|---|
| المؤلفون: | Pan Fan, Guodong Lang, Pengju Guo, Zhijie Liu, Fuzeng Yang, Bin Yan, Xiaoyan Lei |
| المجموعة: | RePEc (Research Papers in Economics) |
| الوصف: | In the vision system of apple-picking robots, the main challenge is to rapidly and accurately identify the apple targets with varying halation and shadows on their surfaces. To solve this problem, this study proposes a novel, multi-feature, patch-based apple image segmentation technique using the gray-centered red-green-blue (RGB) color space. The developed method presents a multi-feature selection process, which eliminates the effect of halation and shadows in apple images. By exploring all the features of the image, including halation and shadows, in the gray-centered RGB color space, the proposed algorithm, which is a generalization of K-means clustering algorithm, provides an efficient target segmentation result. The proposed method is tested on 240 apple images. It offered an average accuracy rate of 98.79%, a recall rate of 99.91%, an F1 measure of 99.35%, a false positive rate of 0.04%, and a false negative rate of 1.18%. Compared with the classical segmentation methods and conventional clustering algorithms, as well as the popular deep-learning segmentation algorithms, the proposed method can perform with high efficiency and accuracy to guide robotic harvesting. ; fruit segmentation; color space; segmentation algorithm |
| نوع الوثيقة: | article in journal/newspaper |
| اللغة: | unknown |
| العلاقة: | https://www.mdpi.com/2077-0472/11/3/273/pdfTest; https://www.mdpi.com/2077-0472/11/3/273Test/ |
| الإتاحة: | https://www.mdpi.com/2077-0472/11/3/273/pdfTest https://www.mdpi.com/2077-0472/11/3/273Test/ |
| رقم الانضمام: | edsbas.62AB9AF7 |
| قاعدة البيانات: | BASE |
| الوصف غير متاح. |