| 基于梯度分布不均匀性的干瘪红枣识别 |
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| 引用本文： | 李功燕,任亦立,马丽艳.基于梯度分布不均匀性的干瘪红枣识别[J].农业机械学报,2016,47(11):213-218. |
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| 作者姓名： | 李功燕 任亦立 马丽艳 |
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| 作者单位： | 中国科学院微电子研究所,江苏物联网研究发展中心;中国科学院大学,中国科学院微电子研究所 |
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| 基金项目： | 国家自然科学基金项目（61402462、61503202 |
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| 摘 要： | 为了从混合的饱满红枣和干瘪红枣中识别出干瘪红枣,首先分析了颜色空间模型的特性,选择灰度图、RGB颜色空间模型的R分量、L*a*b*颜色空间模型的a*分量,并使用不同的梯度算子作为对比;然后通过形态学运算、逻辑运算去除异常梯度,进行梯度归一化变换;最后采用归一化的梯度直方图作为红枣表面的纹理特征表示方法,并计算其梯度分布不均匀性作为判别准则。利用12通道红枣分选机采集240幅饱满与202幅干瘪红枣图像作为样本图像。实验结果表明,采用简单梯度算子对L*a*b*模型的a*分量提取纹理信息效果最好,误判率为0.83%,正确识别率高达99.01%。
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| 关 键 词： | 红枣 机器视觉 识别 梯度分布不均匀性 |
| 收稿时间： | 2016/5/12 0:00:00 |
Recognition of Wizened Red Jujube Based on Ununiformities of Gradient Distribution |
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| Li Gongyan,Ren Yili and Ma Liyan.Recognition of Wizened Red Jujube Based on Ununiformities of Gradient Distribution[J].Transactions of the Chinese Society of Agricultural Machinery,2016,47(11):213-218. |
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| Authors: | Li Gongyan Ren Yili and Ma Liyan |
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| Institution: | Institute of Microelectronics of Chinese Academy of Sciences,Jiangsu R&D Center for Internet of Things; University of Chinese Academy of Sciences and Institute of Microelectronics of Chinese Academy of Sciences |
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| Abstract: | A method of texture feature extraction based on the a* components of L* a* b* color space model was proposed to recognize wizened red jujube from the mix of wizened red jujube and full red jujube. Firstly, grayscale, R component from RGB color space model, a* component from L* a* b* color space model were selected and the gradient values with different gradient operators were calculated respectively. Then, abnormal gradient values were removed by morphological operator and logical operation. Finally, after gradient normalization, the gradient distributions exhibited different behavior for the wizened red jujube and full red jujube. Thus, a texture feature extraction method based on this property was designed, and the recognition of wizened red jujube was achieved. In the experiments, a 12 channel fruits and vegetables sorting machine was used to collect 240 images of full red jujube and 202images of wizened red jujube. The experimental results showed that utilizing a* component from L* a* b* color space model can achieve better recognition rate than utilizing grayscale or R component from RGB color space model; simple gradient operator was more suitable than Sobel gradient operator in texture extraction for wizened red jujube recognition; using the normalized gradient histogram as a texture feature representation and the calculated ununiformities of gradient distribution as discriminant features, the recognition rate was over 99% and the false positive rate was 0.83%. |
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| Keywords: | red jujube computer vision recognition ununiformities of gradient distribution |
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