Abdellahhalimi, and Roukhe, A. and Abdenabi, B. and El Barbri, N. (2013) Sorting dates fruit bunches based on their maturity using camera sensor system. Journal of Theoretical and Applied Information Technology, 56 (3). pp. 324-337.

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Abstract

This paper presents the development and application of image analysis and computer vision system in quality and maturity evaluation of products in the agricultural field. Computer vision is a rapid, consistent and objective inspection technique, which has been expanded to varied industries. Monitoring and controlling ripeness is becoming a very important issue in fruit management since ripeness is perceived by customers as main quality indicator 1. In this paper, we present a method for automatic evaluation of date fruits maturity based on computer vision. The method was implemented, and tested on a sample of dates fruit images with different levels of maturity. Segmentation is one of the basic techniques in computer vision 25. Color is often thought as a property of an individual object and the color of this object comes from the visible light that reflects off the object surface. In this experiment we have implemented a method to quantify the standard color of fruit in HSV(Hue, Saturation and Value) color spaces in order to achieve fruit image segmentation. For this reason, a machine vision system was trained to distinguish between good or mature and yellow or green date fruits. HSV system is suggested as the best color space for quantification in date fruit quality and maturity. In addition, our approach has the benefits of being insensitive to rotation, scaling, and translation. Moreover, the system can be applied to several types of maturity fruit evaluation. In this article we shall give the results of the experiments we have carried out; these results demonstrate the feasibility of our proposed method in color segmentation for date fruit evaluation. © 2005 - 2013 JATIT & LLS. All rights reserved.

Item Type: Article
Subjects: Computer Science
Divisions: SCIENTIFIC PRODUCTION > Computer Science
Depositing User: Administrateur Eprints Administrateur Eprints
Last Modified: 31 Jan 2020 15:46
URI: http://eprints.umi.ac.ma/id/eprint/2716

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