Study on detecting methods for apple stem and defected surface with computer vision
The characteristics of apple stem were studied, the existence of apple stem was detected by scanning. The different reflectance properties of defected surface and non-defected surface of apples were analyzed, the statistical properties of gray value of different pixel were analyzed too. To 15 apple...
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| Format: | Article |
| Language: | English |
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Zhejiang University Press
2001-09-01
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| Series: | 浙江大学学报. 农业与生命科学版 |
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| Online Access: | https://www.academax.com/doi/10.3785/1008-9209.2001.05.0583 |
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| _version_ | 1849412740499636224 |
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| author | ZHANG Wen-ying YING Yi-bin |
| author_facet | ZHANG Wen-ying YING Yi-bin |
| author_sort | ZHANG Wen-ying |
| collection | DOAJ |
| description | The characteristics of apple stem were studied, the existence of apple stem was detected by scanning. The different reflectance properties of defected surface and non-defected surface of apples were analyzed, the statistical properties of gray value of different pixel were analyzed too. To 15 apple pictures without stem, the classification accuracy is 100%, to 90 pictures whose stems are in good condition the accuracy is 88%. This classification lasted about 1 second, the R (Red) value was used to find the suspected defected pixel, the defected area was found by region growing method and the non-defected pixel (including the stem and the calyx) was discarded. Finally, the total defected area of the whole apple was worked out. The tests proved that the method for detecting defected surface was efficient. |
| format | Article |
| id | doaj-art-30adccbf171a44ffb0060509556dfd3d |
| institution | Kabale University |
| issn | 1008-9209 2097-5155 |
| language | English |
| publishDate | 2001-09-01 |
| 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-30adccbf171a44ffb0060509556dfd3d2025-08-20T03:34:21ZengZhejiang University Press浙江大学学报. 农业与生命科学版1008-92092097-51552001-09-012758358610.3785/1008-9209.2001.05.058310089209Study on detecting methods for apple stem and defected surface with computer visionZHANG Wen-yingYING Yi-binThe characteristics of apple stem were studied, the existence of apple stem was detected by scanning. The different reflectance properties of defected surface and non-defected surface of apples were analyzed, the statistical properties of gray value of different pixel were analyzed too. To 15 apple pictures without stem, the classification accuracy is 100%, to 90 pictures whose stems are in good condition the accuracy is 88%. This classification lasted about 1 second, the R (Red) value was used to find the suspected defected pixel, the defected area was found by region growing method and the non-defected pixel (including the stem and the calyx) was discarded. Finally, the total defected area of the whole apple was worked out. The tests proved that the method for detecting defected surface was efficient.https://www.academax.com/doi/10.3785/1008-9209.2001.05.0583computer visionapple stemdefected surfacedetecting methods |
| spellingShingle | ZHANG Wen-ying YING Yi-bin Study on detecting methods for apple stem and defected surface with computer vision 浙江大学学报. 农业与生命科学版 computer vision apple stem defected surface detecting methods |
| title | Study on detecting methods for apple stem and defected surface with computer vision |
| title_full | Study on detecting methods for apple stem and defected surface with computer vision |
| title_fullStr | Study on detecting methods for apple stem and defected surface with computer vision |
| title_full_unstemmed | Study on detecting methods for apple stem and defected surface with computer vision |
| title_short | Study on detecting methods for apple stem and defected surface with computer vision |
| title_sort | study on detecting methods for apple stem and defected surface with computer vision |
| topic | computer vision apple stem defected surface detecting methods |
| url | https://www.academax.com/doi/10.3785/1008-9209.2001.05.0583 |
| work_keys_str_mv | AT zhangwenying studyondetectingmethodsforapplestemanddefectedsurfacewithcomputervision AT yingyibin studyondetectingmethodsforapplestemanddefectedsurfacewithcomputervision |