Research in method to detect size and area of fruits by machine vision
In view of the existing situation of fruits quality detection in our country, which is still dependent on human sense organ to identify and judge the fruits, and the broad application prospect of machine vision in quality evaluation of agricultural products, the method to detect the size and area of...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Zhejiang University Press
2000-05-01
|
| Series: | 浙江大学学报. 农业与生命科学版 |
| Subjects: | |
| Online Access: | https://www.academax.com/doi/10.3785/1008-9209.2000.03.0229 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1850044785070440448 |
|---|---|
| author | YING Yi-bin |
| author_facet | YING Yi-bin |
| author_sort | YING Yi-bin |
| collection | DOAJ |
| description | In view of the existing situation of fruits quality detection in our country, which is still dependent on human sense organ to identify and judge the fruits, and the broad application prospect of machine vision in quality evaluation of agricultural products, the method to detect the size and area of agricultural products b y machine vision was studied. The quantitative relationship between one pixel in the image and the corresponding size and area in the real object was set up, and the new method to calculate the centroid coordinates of the object only based on the boundary information was put forward, which not only offered fast computation because visiting the whole area of the object was not needed, but also provided more accurate estimation since the image texture within the object, such as blemishes, was eliminated from the consideration. It was found that the correlation coefficient of real size versus detected size was 0.96. To decrease the relative errors, the pixel transform method was adopted to recover the geometrical feature of sphere-fruit surface from umbriferous image while the area of defected surface was calculated. Moreover, a new method to revise the estimated area was advanced. These results lay a solid foundation for further developing fruit quality detection system using machine vision. |
| format | Article |
| id | doaj-art-9ea4f73043f8409ca60b8901c6d8104c |
| institution | DOAJ |
| issn | 1008-9209 2097-5155 |
| language | English |
| publishDate | 2000-05-01 |
| publisher | Zhejiang University Press |
| record_format | Article |
| series | 浙江大学学报. 农业与生命科学版 |
| spelling | doaj-art-9ea4f73043f8409ca60b8901c6d8104c2025-08-20T02:54:50ZengZhejiang University Press浙江大学学报. 农业与生命科学版1008-92092097-51552000-05-012622923210.3785/1008-9209.2000.03.022910089209Research in method to detect size and area of fruits by machine visionYING Yi-binIn view of the existing situation of fruits quality detection in our country, which is still dependent on human sense organ to identify and judge the fruits, and the broad application prospect of machine vision in quality evaluation of agricultural products, the method to detect the size and area of agricultural products b y machine vision was studied. The quantitative relationship between one pixel in the image and the corresponding size and area in the real object was set up, and the new method to calculate the centroid coordinates of the object only based on the boundary information was put forward, which not only offered fast computation because visiting the whole area of the object was not needed, but also provided more accurate estimation since the image texture within the object, such as blemishes, was eliminated from the consideration. It was found that the correlation coefficient of real size versus detected size was 0.96. To decrease the relative errors, the pixel transform method was adopted to recover the geometrical feature of sphere-fruit surface from umbriferous image while the area of defected surface was calculated. Moreover, a new method to revise the estimated area was advanced. These results lay a solid foundation for further developing fruit quality detection system using machine vision.https://www.academax.com/doi/10.3785/1008-9209.2000.03.0229fruitssizeareamachine vision |
| spellingShingle | YING Yi-bin Research in method to detect size and area of fruits by machine vision 浙江大学学报. 农业与生命科学版 fruits size area machine vision |
| title | Research in method to detect size and area of fruits by machine vision |
| title_full | Research in method to detect size and area of fruits by machine vision |
| title_fullStr | Research in method to detect size and area of fruits by machine vision |
| title_full_unstemmed | Research in method to detect size and area of fruits by machine vision |
| title_short | Research in method to detect size and area of fruits by machine vision |
| title_sort | research in method to detect size and area of fruits by machine vision |
| topic | fruits size area machine vision |
| url | https://www.academax.com/doi/10.3785/1008-9209.2000.03.0229 |
| work_keys_str_mv | AT yingyibin researchinmethodtodetectsizeandareaoffruitsbymachinevision |