基于特征尺寸及局部极值点的茶鲜叶方向识别
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“十二五”国家科技支撑计划资助项目(2011BAD01B03-4)


Recognition of Fresh Tea Direction Based on Feature Size and Local Extreme Points
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    摘要:

    对粗大茶鲜叶实行梗叶分离,有利于提高成品茶品质,降低能源消耗。梗叶分离的关键在于茶梗与叶柄的识别。通过倾斜滑槽限定茶鲜叶的方位,将其转换为两方向判别问题。首先将茶鲜叶划分为长梗和短梗,对长梗茶鲜叶,提出基于特征尺寸的识别方法,特征尺寸大的一方判为叶尖;对短梗茶鲜叶,提出基于轮廓线局部极值点的识别方法,局部极值点多的一方判为叶尖。通过对168幅随机获取的图像及1幅背景图像的处理表明,茶鲜叶的方向识别率达93.3%。每根茶鲜叶的平均处理时间为17.8 ms,能满足实时处理的要求。

    Abstract:

    Fresh tea leaf and stem separation for coarse tea not only improves the quality of finished tea, but also reduces heat energy consumption. To realize the separation, the key issue is the recognition of tea stems and petioles. Tilted chute was used to constrain the direction of fresh tea. Then, the problem was transformed into determining whether the tea sprout was facing up or down. At first, according to the stem end length, fresh tea was classified into two categories: for those with long stem ends, an algorithm based on the feature size was proposed, and the side with longer feature size was recognized as tea sprout. For those with short stem ends, the “local extreme points of fresh tea contour” was utilized, and the side with more local extreme points was recognized as tea sprout. Then, 168 randomly obtained images and a background image was used to validate the algorithm, and a recognition rate of 93.3% was reached. The average time to recognize the direction of a single fresh tea was 17.8 ms which fulfilled the requirements of real-time processing.

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何雪军,王进,陆国栋,唐小林.基于特征尺寸及局部极值点的茶鲜叶方向识别[J].农业机械学报,2013,44(12):233-238. He Xuejun, Wang Jin, Lu Guodong, Tang Xiaolin. Recognition of Fresh Tea Direction Based on Feature Size and Local Extreme Points[J]. Transactions of the Chinese Society for Agricultural Machinery,2013,44(12):233-238.

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  • 在线发布日期: 2013-12-05
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