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基于圖譜特征的番茄種子活力檢測(cè)與分級(jí)
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國(guó)家重點(diǎn)研發(fā)計(jì)劃項(xiàng)目(2017YFD0701205)和北京市科技計(jì)劃項(xiàng)目(Z151100001015004)


Detection and Classification of Tomato Seed Vitality Based on Image Processing
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    摘要:

    為解決現(xiàn)存分級(jí)過(guò)程中損傷種子問(wèn)題,替代僅根據(jù)種子表面特征評(píng)價(jià)的粗篩查方法,,本研究基于高光譜的圖譜融合技術(shù),,提出了一種番茄種子圖像采集并辨識(shí)種子特征進(jìn)而將種子分級(jí)的算法,。試驗(yàn)隨機(jī)選取170粒番茄種子作為樣品,,校正集與驗(yàn)證集比例約為3∶1,。通過(guò)標(biāo)準(zhǔn)發(fā)芽試驗(yàn)得到種子活力結(jié)果,,基于連續(xù)投影算法(Successive projections algorithm, SPA)求得反映番茄種子活力的特征波長(zhǎng)為:535,、577,、595,、654、684,、713,、744、768,、809,、840nm。對(duì)特征波長(zhǎng)下的光譜圖像進(jìn)行解析,,通過(guò)雙邊濾波法,、大津法、形態(tài)學(xué)變換算法提取了種子邊緣輪廓,,計(jì)算求出每粒種子的面積,、圓形度以及圖像灰度平均值?;诮y(tǒng)計(jì)學(xué)分析,,利用校正集128粒種子的特征值及其標(biāo)準(zhǔn)發(fā)芽試驗(yàn)結(jié)果求出分級(jí)閾值,其中有活力為合格,,無(wú)活力為不合格,。然后,,利用驗(yàn)證集42粒種子的特征值對(duì)閾值進(jìn)行驗(yàn)證,結(jié)果顯示,,在713nm波長(zhǎng)下的圖像特征對(duì)活力結(jié)果判斷分級(jí)的正確率最高,,校正集和驗(yàn)證集的正確率分別為93.75%和90.48%。

    Abstract:

    Precision seeding put forward higher requirements for the seed quality. However, existing grading methods of seeds are destructive and unsuitable for sorting seeds based on internal characteristics, and a classification method based on the seed vitality is required. An algorithm of image acquisition and characteristics identification and classification of tomato seeds was proposed based on hyperspectral technique and image processing technology. Totally 170 grains of tomato seeds were randomly selected as the research object, and the ratio of calibration set and validation set was about 3∶1. Images of tomato seeds were collected by hyperspectral acquisition system which was composed of high performance lighting CCD camera, line scanning spectrometer, oriel instruments, image acquisition card and computer. The resolution of the camera and range of spectrometer were respectively 1376 pixels×1040 pixels and 400~1100nm. An average spectrum of interest region of each seed could be obtained. Then the results of seed vigor were obtained from the standard germination test. And the characteristic wavelengths of tomato seed vigor were acquired by successive projections algorithm (SPA), including 535nm, 577nm, 595nm, 654nm, 684nm, 713nm, 744nm, 768nm, 809nm and 840nm. The images under above characteristic wavelengths were preprocessed by bilateral filtering, Ostu and morphological transformation to gain the seed eigenvalues including area, circularity and average gray. The classification thresholds were calculated according to the eigenvalues and vitality results of the calibration set based on statistical regularity, and prediction analysis of validation set was carried out. The results showed that both of average of area and gray had significant difference between viable seeds and non-viable seeds, while the difference of circularity between viable seeds and non-viable seeds was insignificant. Classification accuracy of calibration and validation sets was above 85% in eight characteristics wavelengths. And 713nm gave the best result, the accuracy of the calibration and validation set were 93.75% and 90.48%, respectively. The results provided a new method for rapid nondestructive grading of tomato seeds, and lay the foundation for the development of tomato seed grading equipment based on seed vitality.

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彭彥昆,趙芳,白京,鄭曉春,王文秀,孫群.基于圖譜特征的番茄種子活力檢測(cè)與分級(jí)[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2018,49(2):327-333. PENG Yankun, ZHAO Fang, BAI Jing, ZHENG Xiaochun, WANG Wenxiu, SUN Qun. Detection and Classification of Tomato Seed Vitality Based on Image Processing[J]. Transactions of the Chinese Society for Agricultural Machinery,2018,49(2):327-333.

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  • 收稿日期:2017-06-05
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  • 在線發(fā)布日期: 2018-02-10
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