| Fruit shape detection by level set |
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| 作者姓名： | GUI Jiang-sheng RAO Xiu-qin YING Yi-bin |
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| 作者单位： | School of Biosystems Engineering and Food Science，Zhejiang University，Hangzhou 310029，China |
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| 基金项目： | 国家自然科学基金
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Program for New Century Excellent Talents in University |
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| 摘 要： | A novel approach for fruit shape detection in RGB space was proposed,which was based on fast level set and Chan-Vese model named as Modified Chan-Vese model(MCV) . This new algorithm is fast and suitable for fruit sorting because it does not need re-initializing. MCV has three advantages compared to the traditional methods. First,it provides a unified frame-work for detecting fruit shape boundary,and does not need any preprocessing even though the raw image is noisy or blurred. Second,if the fruit has different colors at the edges,it can detect perfect boundary. Third,it processed directly in color space without any transformations that may lose much information. The proposed method has been applied to fruit shape detection with promising result.
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| 关 键 词： | 机器视觉 果实形状探测 水平集 三原色空间 |
| 收稿时间： | 21 February 2006 |
| 修稿时间： | 2006-02-212006-05-16 |
Fruit shape detection by level set |
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| GUI Jiang-sheng RAO Xiu-qin YING Yi-bin.Fruit shape detection by level set[J].Journal of Zhejiang University Science,2007,8(8):1232-1236. |
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| Authors: | Gui Jiang-sheng Rao Xiu-qin Ying Yi-bin |
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| Institution: | (1) School of Biosystems Engineering and Food Science, Zhejiang University, Hangzhou, 310029, China |
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| Abstract: | A novel approach for fruit shape detection in RGB space was proposed,which was based on fast level set and Chan-Vese model named as Modified Chan-Vese model(MCV) . This new algorithm is fast and suitable for fruit sorting because it does not need re-initializing. MCV has three advantages compared to the traditional methods. First,it provides a unified frame-work for detecting fruit shape boundary,and does not need any preprocessing even though the raw image is noisy or blurred. Second,if the fruit has different colors at the edges,it can detect perfect boundary. Third,it processed directly in color space without any transformations that may lose much information. The proposed method has been applied to fruit shape detection with promising result. |
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| Keywords: | Machine vision Shape detection Level set Fruit sorting |
| 本文献已被 CNKI 维普 SpringerLink 等数据库收录！ |
