An instance-based learning approach for thresholding in crop images under different outdoor conditio
這篇文章主要是爲了解決包含作物行的圖像灰度化後，二值化所需閾值的選擇問題。 作者主要利用k-means算出訓練集中與之在概率累積圖上相近的k幅圖，然後將這些圖的閾值乘以相應的權重獲得目標圖的二值化閾值。 作者首先利用超綠特徵將圖像灰度化 對灰度化後的圖像生成灰度直方圖，然後對灰度直方圖生成概率直方圖。 選擇多種光照條件下的圖像，並人工選擇合適的閾值，將這些圖像作爲訓練集。 對於目標圖像，利用k-m
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