Date Maturity Status and Classification using Image Processing

Abstract

The main objective of this thesis is to develop an automated system that helps in dates fruit agricultural industry to provide a better quality that satisfies consumers and on the other hand to reduce the potential economic loses. Also, improvements in dates fruit agricultural industry help in giving an appropriate food quantity for people. According to United Nation (UN) statistics, the worldwide population will reach to 9.6 billion by 2050 (United Nations Press Release, 2013), so more good food is needed to avoid the continuous increase in starvation and hunger level. Dates are known as a good food source, but there are a lot of challenges in harvesting it such like the lack of experts. people in that field. In this work, an automated system is developed that can identify different dates fruit maturity status and classify their categories by using the various techniques provided by image processing technology. The system used the different dates fruit features such as color, size and skin texture. The developed system could count the number of harvested fruits and label them. Also, dates category is classified by the system by extracting the object color or comparing the object size. Finally, defects can be identified by detecting the cold area in a thermal image. The results showed that the developed system is helpful and could improve the dates fruit agricultural industry quality.