A Comparative Analysis of Feature Extraction Methods for Fruit Grading Classillcations
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Date
2013
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Abstract
Fruit plays an important role in our life. India is exporting large number o f fruits to abroad in that
mosambi is one among. Before exporting the fruits, the fruits have to be graded according to their quality. This
paper presents an evaluation and comparison o f the performance o f three different extraction methods for
classification of defect and non defect fruits. Three different feature extraction methods are GLCM (Grey Level
Co-occurrence Matrix), shape features and intensity based features. The performance of each feature extraction
method is evaluated and compared based on PNN (Probabilistic Neural Network) classifier. The experimental
results suggest that shape feature outperformed than other two methods.