农业工程学报
農業工程學報
농업공정학보
2010年
3期
216-221
,共6页
钟取发%周平%付斌斌%刘科文
鐘取髮%週平%付斌斌%劉科文
종취발%주평%부빈빈%류과문
图像处理%计算机视觉%测量%轮廓匹配%形状上下文%多边形近似
圖像處理%計算機視覺%測量%輪廓匹配%形狀上下文%多邊形近似
도상처리%계산궤시각%측량%륜곽필배%형상상하문%다변형근사
image processing%computer vision%measurements%contour matching%shape context%polygonal approximation
为了定量化评估农作物的虫害程度,提出了一种基于典型叶片模板自动匹配的叶片虫损面积测量新方法.先将叶片图像二值化并提取其外轮廓;再对提取的轮廓进行多边形近似,以多边形的顶点为端点将叶片外轮廓划分成若干子轮廓;然后采用形状上下文对完整叶片与虫损叶片之间的子轮廓进行自动配准,找出其间的相互映射关系;最后根据映射关系对虫损叶片进行重建,计算出虫损面积.对10类不同叶片的测量分析表明:该方法平均每叶片耗时0.962 s,最大相对误差为8.22%,平均相对误差为4.78%.其中,形状复杂度高的叶片平均相对误差为7.48%,复杂度中等的叶片为5.99%,复杂度低的叶片为1.84%.结果表明,该方法能准确而快速地测量虫损叶面积.
為瞭定量化評估農作物的蟲害程度,提齣瞭一種基于典型葉片模闆自動匹配的葉片蟲損麵積測量新方法.先將葉片圖像二值化併提取其外輪廓;再對提取的輪廓進行多邊形近似,以多邊形的頂點為耑點將葉片外輪廓劃分成若榦子輪廓;然後採用形狀上下文對完整葉片與蟲損葉片之間的子輪廓進行自動配準,找齣其間的相互映射關繫;最後根據映射關繫對蟲損葉片進行重建,計算齣蟲損麵積.對10類不同葉片的測量分析錶明:該方法平均每葉片耗時0.962 s,最大相對誤差為8.22%,平均相對誤差為4.78%.其中,形狀複雜度高的葉片平均相對誤差為7.48%,複雜度中等的葉片為5.99%,複雜度低的葉片為1.84%.結果錶明,該方法能準確而快速地測量蟲損葉麵積.
위료정양화평고농작물적충해정도,제출료일충기우전형협편모판자동필배적협편충손면적측량신방법.선장협편도상이치화병제취기외륜곽;재대제취적륜곽진행다변형근사,이다변형적정점위단점장협편외륜곽화분성약간자륜곽;연후채용형상상하문대완정협편여충손협편지간적자륜곽진행자동배준,조출기간적상호영사관계;최후근거영사관계대충손협편진행중건,계산출충손면적.대10류불동협편적측량분석표명:해방법평균매협편모시0.962 s,최대상대오차위8.22%,평균상대오차위4.78%.기중,형상복잡도고적협편평균상대오차위7.48%,복잡도중등적협편위5.99%,복잡도저적협편위1.84%.결과표명,해방법능준학이쾌속지측량충손협면적.
In order to evaluate the pest-damaged extent of crop quantitatively, the anthors proposed a novel method based on auto-matching of representative whole leaf to measure leaf pest-damaged area. Firstly, the outer contour of leaf was extracted after image binary; secondly, the contour was approximated to a polygon and segmented to many sub-contours using polygon vertexes; thirdly, the mapping relationship between the whole leaf and the pest-damaged leaf was constructed by matching their sub-contours based on the shape context; finally, the pest-damaged leaf was reconstructed by mapping their sub-contour relationship for area calculation. The experiments on ten types of different leaves showed that the average process time for one leaf was 0.952 s, the maximum relative error was 8.22% and, the average relative error was 4.78%. As to leaves with high shape complexity, the average relative error was 7.48%, and to leaves with medium and low shape complexity, those were 5.99% and 1.84%, respectively. The proposed method has proved to be an accurate and efficient method for measurement of leaf pest-damaged area.