ESTIMATION OF TIP SHAPE FOR CARROT CLASSIFICATION BY MACHINE VISION

被引:21
作者
HOWARTH, MS [1 ]
BRANDON, JR [1 ]
SEARCY, SW [1 ]
KEHTARNAVAZ, N [1 ]
机构
[1] TEXAS A&M UNIV SYST,DEPT AGR ENGN,COLL STN,TX 77843
来源
JOURNAL OF AGRICULTURAL ENGINEERING RESEARCH | 1992年 / 53卷 / 02期
关键词
D O I
10.1016/0021-8634(92)80078-7
中图分类号
S2 [农业工程];
学科分类号
0828 ;
摘要
Tip shape has been identified as an important carrot feature which is a major concern to both consumers and in post harvest operations. A classification method can help carrot breeders to measure the success of their breeding operations. Based on the Freeman chain code, a curvature profile was developed. Using a non-linear least squares technique known as the Marquardt method, the curvature profile was reduced to six parameters describing the carrot tip. These parameters were used to develop a Bayes decision function which classified carrot tips into five classes (sharp tapered to extremely blunt tips). This method was tested on 250 carrots. Of the 250 carrots tested, 14% were misclassified. © 1992 Silsoe Research Institute.
引用
收藏
页码:123 / 139
页数:17
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