Myint San; Mie Mie Aung; Phyu Phyu Khaing

Fruit Recognition Using Color and Morphological Features Fusion

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Author(s)

Myint San ^1,* Mie Mie Aung ¹ Phyu Phyu Khaing ²

1. Faculty of Information Science, University of Computer Studies (Monywa), Myanmar

2. Faculty of Information Science, Myanmar Institute of Information Technology, Mandalay, Myanmar

* Corresponding author.

DOI: https://doi.org/10.5815/ijigsp.2019.10.02

Received: 7 Aug. 2019 / Revised: 13 Aug. 2019 / Accepted: 27 Aug. 2019 / Published: 8 Oct. 2019

Index Terms

Fruit recognition, feature fusion, color feature, morphological feature

Abstract

It is still difficult to recognize the kind of fruit which are of different colors, shapes, and textures. This paper proposes a features fusion method to recognize five different classes of fruits that are the images from the fruit360 dataset. We are processed with four stages: pre-processing, boundary extraction, feature extractions, and classification. Pre-processing is performed to remove the noise by using the median filter, and boundary extraction are operated with the morphological operation. In feature extraction, we have extracted two types of features: color, and morphological features of the image. Color features are extracted from the RGB color channel, and morphological features are extracted from the image that detected the boundary of fruit by using morphological operations. These two types of features are combined in a single feature descriptor. These features are passed to five different classifiers: Naïve Bayes (NB), Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), K-Nearest Neighbor (KNN), and Random Forest (RF). In the study, the accuracy that classified with Random Forest (RF) classifier for the proposed feature fusion method is better than the other classifiers, such as Naïve Bayes (NB), Logistic Regression (LR), Support Vector Machine (SVM), Decision Tree (DT), K-Nearest Neighbor (KNN).

Cite This Paper

Myint San, Mie Mie Aung, Phyu Phyu Khaing, "Fruit Recognition Using Color and Morphological Features Fusion", International Journal of Image, Graphics and Signal Processing(IJIGSP), Vol.11, No.10, pp. 8-15, 2019. DOI: 10.5815/ijigsp.2019.10.02

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International Journal of Image, Graphics and Signal Processing (IJIGSP)