Study on background segment and edge detection of fruit image using machine vision
In the light of the characteristics of gray level variations in the image, bimodal gray region segment method was adopted to segment the pear from the background in the three images (red, green, blue). The best segment result was appeared in B gray level histogram. Four different edge operator were...
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| Main Author: | |
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| Format: | Article |
| Language: | English |
| Published: |
Zhejiang University Press
2000-01-01
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| Series: | 浙江大学学报. 农业与生命科学版 |
| Subjects: | |
| Online Access: | https://www.academax.com/doi/10.3785/1008-9209.2000.01.0035 |
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| Summary: | In the light of the characteristics of gray level variations in the image, bimodal gray region segment method was adopted to segment the pear from the background in the three images (red, green, blue). The best segment result was appeared in B gray level histogram. Four different edge operator were used to extract the step-like edge of the fruit image, and the Hilditch thinning method was used to fulfil edge thinning. As the results shown, the adopted method of background segment and edge detection could satisfy the requirement of detecting size, shape, stem, and surface defect of fruit. |
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| ISSN: | 1008-9209 2097-5155 |