AN AUTOMATED SYSTEM FOR DATE FRUIT RECOGNITION THROUGH IMAGES

Abstract

Date is a fruit with a great health and economic benefits. However, farmers plant a little number of varieties and too little are known by people. Therefore, there is an urgent need to preserve such an important cultural heritage for the next generations.In this paper, we present an automated system for date fruit recognition from their images. Specifically, we collect fifty (50) samples from seven (7) varieties, and then we take images for those samples. Afterwards, and in order to identify the visual characteristics of samples belonging to each variety, we extract shape and color features from the images.Then, we use the Support Vector Machine (SVM) classifier to optimally separate the visual characteristics of the different varieties. Later on, SVM is used to decide for a test sample the variety it belongs to. Our system presents a multitude of advantages: 1) it is able to accurately recognize dates in spite of the large variation within some varieties (intra-variation) and the small variation between some varieties (inter-variation); 2) no physical measurements are needed, and only visual characteristics of sample images are sufficient; and 3) it doesn‟t require any human intervention. Experimental results, carried out on the samples we collected, show a high recognition rate of 97.14%.