【摘要】：為準(zhǔn)確定位疊貼情況下的葡萄目標(biāo),提出了一種基于輪廓分析的雙串疊貼葡萄目標(biāo)識別方法。首先提取最能突顯夏黑葡萄的HSV顏色空間中的H分量,通過改進(jìn)K-means聚類方法對葡萄圖像進(jìn)行分割,運(yùn)用形態(tài)學(xué)去噪等處理獲取葡萄圖像區(qū)域,再提取該區(qū)域邊緣輪廓和左右輪廓的類圓中心。然后以該中心點(diǎn)為原點(diǎn)建立基于輪廓分析的疊貼葡萄串分界線幾何求解與計算模型,分別在逆時針方向45°~135°和225°~315°區(qū)域內(nèi)沿葡萄輪廓搜索距離原點(diǎn)最近的點(diǎn),進(jìn)而確立兩疊貼葡萄輪廓拐點(diǎn)及其分界線,最終實(shí)現(xiàn)對疊貼葡萄目標(biāo)的分別提取。對從果園采集的27幅雙串疊貼葡萄圖像進(jìn)行試驗(yàn),結(jié)果顯示:24幅圖像中的疊貼葡萄串被正確識別和提取,成功率達(dá)88.89%,目標(biāo)像素區(qū)域的識別精準(zhǔn)度為87.63%~96.12%,算法處理時間在0.59~0.68 s之間。將算法移植到自主研制的機(jī)器人上進(jìn)行視覺定位試驗(yàn),結(jié)果表明所提方法可很好地用于兩疊貼葡萄目標(biāo)的識別與定位。
[Abstract]:In order to accurately locate grape targets under overlapping conditions, a double-string overlapping grape target recognition method based on profile analysis is proposed. Firstly, the H component in the HSV color space of summer black grape is extracted, the grape image is segmented by improved K-means clustering method, and the grape image region is obtained by morphological denoising, and then the edge outline and the center of the left and right contours of the region are extracted. Then, taking the center point as the origin, the geometric solution and calculation model of overlapping grape string dividing line based on outline analysis are established. The nearest point to the origin is searched along the grape outline in the counterclockwise direction of 45 擄~ 135 擄and 225 擄~ 315 擄, respectively, and then the inflection point and dividing line of the two stacked grape contours are established, and finally the target of stacked grape is extracted respectively. 27 double-string overlapping grape images collected from orchards were tested. The results showed that the success rate was 88.89%, the recognition accuracy of target pixel region was 87.63% and 96.12%, and the processing time of the algorithm was between 0.59 and 0.68 s, the success rate was 88.89%, the accuracy of target pixel region was 87.63% and 96.12%, and the processing time of the algorithm was 0.59 鈮，

本文編號：2524875