摘要
为了能够快速准确地计算出类圆果实的形心坐标和半径,提出了一种基于改进圆形随机Hough变换的快速类圆果实目标检测方法。在以2R-G色差分量实现背景分离后,采用模板匹配细化算法获取单像素果实轮廓,并按步长获取果实的边缘特征点;然后,根据边缘特征点的平均切线方向对特征点进行分组,并以此为依据对圆形RHT算法进行改进;最后利用改进后的圆形RHT算法计算出类圆果实的形心坐标和半径。该方法能够快速准确地对类圆果实进行检测,对部分被遮挡的类圆果实识别效果较好。
In order to calculate accurate centric coordinates and radius of quasi-circular fruit rapidly,a kind of detection method for quasi-circular fruits based on improved randomized circular Hough transform was proposed.After the object was segmented from background with 2R-G,the template matching thinning algorithm was used to extract one-pixel fruit contour,from which the edge character points were abstracted.Then the edge character points were grouped according to their average tangent directions,with which the circular RHT algorithm was improved.Last,the centric coordinates and radius of quasi-circular fruits were calculated with the optimized circular RHT algorithm.The proposed method can detect the quasi-circular fruits rapidly and accurately,and can also recover the shape of part-covered fruit satisfactorily.
出处
《农业工程学报》
EI
CAS
CSCD
北大核心
2010年第7期157-162,共6页
Transactions of the Chinese Society of Agricultural Engineering
基金
国家"863"计划项目(2006AA10Z259)
南京农业大学青年科技创新基金项目(kj08027)
关键词
目标识别
算法
研究
类圆形
方向编码
边缘特征点
object recognition
algorithms
research
quasi-circular
direction coding
edge character point
