| 多梯度流域变换算法与传统算法比较 |
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| 引用本文： | 朱昊,刘文耀,王金涛,郑伟,郝永杰,左坤隆.多梯度流域变换算法与传统算法比较[J].天津大学学报(自然科学与工程技术版),2004,37(1):37-40. |
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| 作者姓名： | 朱昊 刘文耀 王金涛 郑伟 郝永杰 左坤隆 |
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| 作者单位： | [1]天津大学精密仪器与光电子工程学院,光电信息技术科学教育部重点实验室,天津300072 [2]中国大恒集团有限公司北京图像视觉技术分公司,北京100086 |
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| 基金项目： | 国家863光电子主题307资助项目(863 307 14 4(02)). |
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| 摘 要： | 流域变换是图像分割的有力工具，流域分割方法的性能主要依赖于图像梯度。文中利用传统单尺度梯度算子流域分割算法和多尺度形态梯度流域变换算法，分别作用于计算机视觉细胞图像和水果图像，结果显示传统分割算法和多尺度算子流域分割算法在不同的图像中显示出各自的优越性，第一种算法更适合于交叠区域不是很多，但质地不必十分均匀的图像；第二种则更适合于交叠区域较多，质地较均匀的图像。
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| 关 键 词： | 流域分割 多尺度梯度算子 结构元素 膨胀 腐蚀 算法 流域变换 图像分割 计算机视觉 |
| 文章编号： | 0493-2137(2004)01-0037-04 |
| 修稿时间： | 2002年10月16 |
Comparison Between Conventional Operator and Multi-Scale Gradient Watershed Transformation Operator |
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| ZHU Hao,LIU Wen-yao,WANG Jin-tao,ZHENG Wei,HAO Yong-jie,ZUO Kun-long f Ministry of Education,School of Precision Instruments and Opto-Electronic Engineering,Tianjin University Tianjin ,China.Comparison Between Conventional Operator and Multi-Scale Gradient Watershed Transformation Operator[J].Journal of Tianjin University(Science and Technology),2004,37(1):37-40. |
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| Authors: | ZHU Hao LIU Wen-yao WANG Jin-tao ZHENG Wei HAO Yong-jie ZUO Kun-long f Ministry of Education School of Precision Instruments and Opto-Electronic Engineering Tianjin University Tianjin China |
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| Affiliation: | ZHU Hao~1,LIU Wen-yao~1,WANG Jin-tao~2,ZHENG Wei~1,HAO Yong-jie~1,ZUO Kun-long~1 f Ministry of Education,School of Precision Instruments and Opto-Electronic Engineering,Tianjin University Tianjin 300072,China, 2. Beijing Image Vision Technology Branch,China Daheng Group Inc,Beijing 100086,China) |
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| Abstract: | Watershed transformation is a powerful morphological tool for image segmentation. The performance of segmentation methods based on watershed depends largely on the gradient of the image. The conventional transformation and the new one of watershed based on multi-scale gradient operator are discussed in this paper. They are used in cell and fruit images respectively. The results demonstrate the two methods have their own advantages respectively.The first one works better with an image of less overlapped objects in the irregular back-ground. On the contrary, the second one is well applied to images of more overlapped objects in regular background. |
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| Keywords: | watershed segmentation multi-scale gradient operator structuring element dilation erosion |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
