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基于線陣掃描圖像的玉米果穗性狀檢測技術(shù)
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“十二五”國家科技支撐計(jì)劃資助項(xiàng)目(2012BAD31B09)


Detecting Techniques of Maize Ear Characters Based on Line Scan Image
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    為實(shí)現(xiàn)玉米果穗性狀自動檢測,以線陣掃描方式獲取玉米果穗表面圓周圖像信息,利用圖像處理技術(shù)從中提取相關(guān)性狀參數(shù)。從掃描圖像自身提取檢測模板,應(yīng)用歸一化互相關(guān)算法完成玉米果穗單周圖像的精確切割;以O(shè)tsu法完成籽粒分割后,利用邊界非完整籽粒的連接性,完成邊界分割籽粒的合并,提高籽粒計(jì)數(shù)準(zhǔn)確度;采用圖像投影曲線平滑后求極值的方法獲取穗行數(shù)。與人工檢測實(shí)驗(yàn)結(jié)果對比,穗粒數(shù)和穗行數(shù)的計(jì)數(shù)準(zhǔn)確率分別為94.6%和99.1%。

    Abstract:

    To acquire the properties of ear characters in maize automatically, a panorama of the maize ear was captured by using a line scan camera. Then the data was extracted through image processing methods. A part of the original line scan image was selected as a template. The ear image with exactly 360° views was cropped according to the normalized cross correlation of the template with the original image. Otsu method was used to segment the maize kernels, but the kernels on the image borders were split into two parts. The connectivity of those two parts of one kernel on both borders was taken as a clue to merge them into ones. This process improved the counting accuracy of kernel numbers. The row number of the kernel was obtained from the image projection method. The profile of projection was smoothed to solve the extreme points as the row number. Experiment results showed the counting accuracy of kernels numbers and kernel rows numbers were 94.6% and 99.1%, respectively.

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柳冠伊,楊小紅,白 明,魏文軍,張紹英,李海濤.基于線陣掃描圖像的玉米果穗性狀檢測技術(shù)[J].農(nóng)業(yè)機(jī)械學(xué)報,2013,44(11):276-280. Liu Guanyi, Yang Xiaohong, Bai Ming, Wei Wenjun, Zhang Shaoying, Li Haitao. Detecting Techniques of Maize Ear Characters Based on Line Scan Image[J]. Transactions of the Chinese Society for Agricultural Machinery,2013,44(11):276-280.

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  • 在線發(fā)布日期: 2013-11-07
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