iPepper: Intelligent pepper grading and quality assurance system

Abstract

Pepper is a key export of the state of Sarawak (Malaysian Borneo); it produces 98% of Malaysia's pepper. At present, processed pepper berries are graded manually. This process is time consuming and error prone as it is very much dependent on the experience of the pepper grader. To overcome these weaknesses, we propose a Pepper Grading System which employs image processing and machine learning approaches using image features and moisture content data of the pepper berries. For instance, from initial tests, a high correlation between the grade of pepper berries to the colour features has been detected. Using existing machine learning algorithms in WEKA, we have obtained a 100% accuracy in categorising the pepper berries into the correct grades. In addition, moisture content and colourometer readings provide another 2 other parameters which may complement the image features in accurately classifying the berries into the right grades.