Abstract- The coffee is one of the most important product for the acquisition of foreign currency. The quality of a coffee bean is determined by several factors including color, texture, and size. High quality beans are carefully refined where defects, such as black beans, are removed. The assessment through visual inspection may be subjected to external factors such as light and the amount of beans to be inspected. This study presents a method of controlling the coffee bean quality using Image Processing techniques. Due to its massive trading in world markets, maintaining the quality of coffee is vital for the exporting countries. One approach for quality control is to have a system that can classify coffee beans based on the quality. This system can assist the small-medium coffee enterprises to monitor and secure their procurement. However, the coffee beans quality classification technology is currently unavailable to the small-medium coffee enterprises community. To address this issue, we developed a mobile application powered by a deep-learning-based model to automatically classify coffee beans quality via a mobile phone camera. The deep learning model used is chosen between AlexNet and VGG19 based on their performance to classify coffee beans quality.

Keywords: Coffee, Coffee Beans, classification, deep learning, Image Processing, Defect, convolutional neural network, deep neural network, CNN, Image Processing, artificial neural network.

| DOI: 10.17148/IARJSET.2022.9725