Feature Fusion Based Orange and Banana Fruit Quality Analysis with Textural Image Processing

Abstract

A nondestructive approach for fruit quality assessment is outlined. Fruit Quality is determined by external and internal features. Only external features won’t help to determine the overall quality of a fruit. Color images and x-ray image of Orange and Banana fruit are captured. With Image processing tool features like Color histogram, color moments and Gabor filter are extracted for external as well as internal quality assessment. Total 18 color features and 27 textural features are extracted for analysis. Sample color images and x-ray image of Orange and Banana fruit are trained and tested. Fusion algorithm is developed to detect the fruit class. Fruits are divided into three classes’ viz. 50% defected, 90% defected and Normal class. SVM and ANN classifier are elected to determine the fruit quality. This information is used to determine degradation level of a fruit. The experimental result showed that % accuracy with SVM classifier is more than ANN classifier.