WAVELET-BASED FEATURE EXTRACTION TECHNIQUE FOR FRUIT SHAPE CLASSIFICATION

被引：0

作者：

Riyadi, Slamet ^{[1
]}

Ishak, Asnor Juraiza ^{[1
]}

Mustafa, Mohd Marzuki ^{[1
]}

Hussain, Aini ^{[1
]}

机构：

[1] Univ Kebangsaan Malaysia, Dept Elect Elect & Syst Engn, Ukm Bangi 43600, Selangor, Malaysia

来源：

2008 5TH INTERNATIONAL SYMPOSIUM ON MECHATRONICS & ITS APPLICATIONS, SYMPOSIUM PROCEEDINGS | 2008年

关键词：

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

For export, papaya fruit should be free of defects and damages. Abnormality in papaya fruit shape represents a defective fruit and is used as one of the main criteria to determine suitability of the fruit to be exported. This paper describes a wavelet-based technique used to perform feature extraction to extract unique features which are then used in the classification task to discriminate deformed papaya fruits from well formed fruits using image processing approach. The extracted features, when used in the classification task using linear discriminant analysis (LDA), afford accuracy of more than 98%..

引用

页码：376 / 380

页数：5

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