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基于顏色分量運(yùn)算與色域壓縮的雜草實(shí)時(shí)檢測(cè)方法
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    摘要:

    提出了一種基于RGB分量運(yùn)算和色域位屏蔽壓縮的雜草實(shí)時(shí)檢測(cè)方法,。對(duì)雜草和作物的大量實(shí)驗(yàn)顯示:顏色分量運(yùn)算可增強(qiáng)目標(biāo)的顯示特性,,而對(duì)色域的屏蔽壓縮可在保證實(shí)時(shí)性的同時(shí)減弱圖像噪聲污染,,減小干擾引起的紋理分割誤差。該方法的處理時(shí)間幾乎不受目標(biāo)復(fù)雜度影響,可在30 ms內(nèi)有效分割出320×240分辨率圖像中有顏色差異的不同雜草或農(nóng)作物,,對(duì)顏色分布波動(dòng)具有較強(qiáng)的魯棒性。顏色分量運(yùn)算的線性組合系數(shù)可通過有監(jiān)督的學(xué)習(xí)自動(dòng)確定。

    Abstract:

    A real-time method to extract weed or crop populations was presented, based on RGB color components operation combined with bit-masked color reduction. Experimental results on different weed or crop populations show that color components operation can enhance the visual pattern of objects to human, and color bit-masked operation can reduce noises in image, so that the error on segmentation can be reduced. Processing time of this method costs little, no matter how complex of related scenario, with color objects be extracted within 30 ms for images of 320×240 resolution, and it's robust to variation of color or illumination on local weed or crop populations. The coefficient and operator for color components combination is determined by a supervised learning mechanism.

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周平,汪亞明,趙勻.基于顏色分量運(yùn)算與色域壓縮的雜草實(shí)時(shí)檢測(cè)方法[J].農(nóng)業(yè)機(jī)械學(xué)報(bào),2007,38(1):116-119.[J]. Transactions of the Chinese Society for Agricultural Machinery,2007,38(1):116-119.

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