Articles
DATE FRUIT SORTING USING APPEARANCE-BASED INFORMATION AND NEURAL NETWORK CLASSIFIER
Article number
1054_32
Pages
271 – 277
Language
English
Abstract
This paper presents a new two-step system for automatically sorting date fruit in four categories which are big Sukkari dates, defective big Sukkari dates, small Sukkari dates and Khalas dates.
In the first step, we used the Principal Component Analysis tool for feature extraction and data dimensionality reduction.
Then, the obtained features were injected in a modified Back-Propagation-based Neural Network to be classified.
Four tests were made upon a locally made database of date images, and obtained results varied between 96 and 100% accuracy.
In the first step, we used the Principal Component Analysis tool for feature extraction and data dimensionality reduction.
Then, the obtained features were injected in a modified Back-Propagation-based Neural Network to be classified.
Four tests were made upon a locally made database of date images, and obtained results varied between 96 and 100% accuracy.
Authors
H. Bouchech, S. Foufou, L. Khriji
Keywords
date fruit, principal component analysis, neural network
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