Leaf plant identification system based on hidden naive bays classifier

被引:6
作者
Eid, Heba F. [1 ,5 ]
Hassanien, Aboul Ella [2 ,3 ,5 ]
Kim, Tai-Hoon [4 ]
机构
[1] Al Azhar Univ, Fac Sci, Cairo, Egypt
[2] Cairo Univ, Fac Comp & Informat, Cairo, Egypt
[3] BeniSuef Univ, Fac Comp & Informat, Bani Suwayf, Egypt
[4] Sungshin Womens Univ, Dept Convergence Secur, Seoul, South Korea
[5] SRGE, Cairo, Egypt
来源
2015 4TH INTERNATIONAL CONFERENCE ON ADVANCED INFORMATION TECHNOLOGY AND SENSOR APPLICATION (AITS) | 2015年
关键词
plant identification; Plant biometrics; Classification; Hidden naive bays; SHAPE;
D O I
10.1109/AITS.2015.28
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Plant identification is vital for the management of plant species. An automated plant identification system is required for the characterization of plant species without requiring the expertise of botanists. This paper presents an efficient and computational model for plant species identification using digital images of leaves. The proposed identification system combines the leaf biometric features, where shape and venation features are used for leaf image classification. 10 combined biometric leaf features are extracted and passed to Hidden naive bays classifiers to be categorized. Several experiments are conducted and demonstrated on 1907 sample leaves of 32 different plant species taken form Flavia dataset. Where, the proposed plant identification model shows consistently performances of 97% average identification accuracy.
引用
收藏
页码:76 / 79
页数:4
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