Machine vision system used for real - time detection inter - row weeds 結合顏色和形態(tài)特征的雜草實時識別方法
In this paper we study the method to detect the inter - row weeds in wheat field 本文就進行了基于圖像處理技術的麥田行間雜草的實時識別方法的研究。
5 . the seed fill algorithm in graphics was introduced into the between - rows weed detection to fill the areas connected with the centre of the crop row . in order to gain the faster processing speed , an improved scan - line seed fill algorithm was developed successfully 根據雜草多數分布于作物行之間的裸土區(qū)的位置特征,首次引入圖形學中的種子填充算法識別行間雜草,并且針對傳統(tǒng)種子填充算法比較費時的缺點,研究改進的掃描線種子填充算法,顯著提高了填充速度。
3 . because of the severe occluding of drilling crop leaves , it was difficult to extract shape and texture feature , so a new approach to detect the between - rows weed was discussed on the basis of the position feature , where crop was regularly sown as a constant row space and most weed were distributed on the bare - soil between crop rows during 3 leaves to 5 leaves seedling stage 針對小麥等條播作物田間場景中葉片嚴重交疊致使形狀和紋理特征提取困難的問題,利用條播作物3 5葉苗期田間場景中作物成行排列、雜草多數分布于作物行之間的裸土區(qū)的特點,研究了位置特征識別行間雜草的方法。