| 梨果面坏损区域的计算机视觉检测方法 |
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| 引用本文： | 梁伟杰,邓继忠,张泰岭. 梨果面坏损区域的计算机视觉检测方法[J]. 农业机械学报, 2005, 36(7): 101-103 |
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| 作者姓名： | 梁伟杰 邓继忠 张泰岭 |
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| 作者单位： | 华南农业大学工程学院;华南农业大学工程学院;华南农业大学工程学院 |
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| 基金项目： | 广东省教育厅自然科学研究资助项目(项目编号:粤教科[2001]72号) |
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| 摘 要： | 为检测梨的果面的坏损区域,提出了一种利用多台摄像机在多个角度进行拍摄,对多幅采集后的图像进行切割,提取各自特征并进行拼合的算法。试验证明,这是一种较为快速、准确检测梨的果面坏损区域大小的算法,识别梨的坏损面积的相对误差能控制在±0.2范围内,处理时间为250～350ms;识别梨坏损区域数的正确率为0.89,可以满足系统设计要求。
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| 关 键 词： | 梨 果面缺陷 计算机视觉 检测 |
| 修稿时间： | 2004-06-17 |
Study on Computer Vision Inspecting for Pear Surface Defect |
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| Liang Weijie,Deng Jizhong,Zhang Tailing. Study on Computer Vision Inspecting for Pear Surface Defect[J]. Transactions of the Chinese Society for Agricultural Machinery, 2005, 36(7): 101-103 |
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| Authors: | Liang Weijie Deng Jizhong Zhang Tailing |
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| Affiliation: | South China Agricultural University |
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| Abstract: | Aiming at inspecting of the pear surface defect, a new algorithm was bring forward by shooting pear surface from various directions using multi-cameras, cutting and recomposing the images into a new one. The experiments prove that the relative error of pear defect area is in the rang of 0.2, the veracity of pear surface defect number is up to 0.89, processing time is 250~350 ms. The new algorithm can meet the requirement of the real-time inspecting. |
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| Keywords: | Pear Surface defect Computer vision Inspecting |
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