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System for automatic separation of sugar cane top

机译：自动分离甘蔗顶部的系统

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In Japan, mechanical sugarcane harvesting has been introduced in many regions. It improves the efficiency of sugarcane harvesting, but also brings the cane tops into sugar factories, which decreases the yield and causes economic losses. This study investigated a system that can distinguish cane tops from the mechanically harvested raw sugarcane materials. We used a green He-Ne laser (wavelength 543.5nm, output 4mW) to scan the raw sugarcane materials and measured the back-reflected light intensity by a light sensor (avalanche photodiode module). Since the surface roughness is different between cane top and cane stalk, analyzing the different patterns of the distribution of the back-reflected light intensity enables the cane top and stalk to be distinguished. In the experiment, 22 cane tops and 32 cane stalks were used as samples. Using kurtosis as a parameter to analyze the patterns, the percentage of correctly identifying cane tops was 90.9, and that of cane stalks was 71.9, and the percentage of correct answers of all samples was 79.6.
机译：在日本，许多地区都引进了机械甘蔗收割机。它提高了甘蔗收割的效率，但也将甘蔗条带入制糖厂，这降低了产量并造成了经济损失。这项研究研究了一种系统，该系统可以将甘蔗顶部与机械收获的原始甘蔗原料区分开。我们使用绿色He-Ne激光器（波长543.5nm，输出4mW）扫描甘蔗原料，并通过光传感器（雪崩光电二极管模块）测量了背反射光强度。由于甘蔗顶部和甘蔗茎之间的表面粗糙度不同，因此分析背向反射光强度分布的不同模式可以区分甘蔗顶部和甘蔗。在实验中，使用22个甘蔗茎和32个甘蔗茎作为样品。以峰度为参数分析模式，正确识别出的茎顶比例为90.9，茎秆的正确识别率为71.9，所有样品的正确答案的比例为79.6。

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