Leaf classification based on Shape and Edge feature with k-NN Classifier

被引：0
|
作者：
Kumar, Pullela S. V. V. S. R. [1 ]
Rao, Konda Naga Venkateswara [2 ]
Raju, Akella S. Narasimha [2 ]
Kumar, D. J. Nagendra [3 ]
机构：
[1] Aditya Coll Engn, Dept CSE, Surampalem, India
[2] VSM Coll Engn, Dept CSE, Ramachandrapuram, India
[3] Vishnu Inst Technol, Dept IT, Bhimavaram, India
来源：
PROCEEDINGS OF THE 2016 2ND INTERNATIONAL CONFERENCE ON CONTEMPORARY COMPUTING AND INFORMATICS (IC3I) | 2016年
关键词：
Leaf classification; shape features; edge features; k-nearest neighbor; Flavia database;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this paper a new approach is proposed to classify leafs in efficient and effective manner. In this approach, the features are extracted from edges of the leaf images and it is used two kinds of features which are edge based and shape based features for leaf classification. When the present method is tested on Flavia dataset, it gives the average classification accuracy rate of 94.37%. The Flavia dataset contains 32 kinds of plant leaves. The experimental result shows that the method gives better performance results compared with existing methods.
引用
收藏
页码：548 / 552
页数：5
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