A Research Project Submitted In Partial Fulfillment Of The Requirements For Degree Of Masters Of Science (Msc) In Information Science (Ikm)

Abstract

Coffee is a beverage obtained from cherry, the fruit of coffee plant. Scaling or grading serve as a process for controlling the quality of an agricultural commodity so that buyer and seller can do business without personally examining every lot sold. This study attempts to apply digital image processing techniques towards sample coffee raw quality value scaling1. More specifically, this study focuses in the extraction and selection of the decisive coffee bean features that are useful for the purpose of classification of the raw quality sample coffee beans by designing, analyzing and testing an automated image processing model. The research design employed in this study is experimental research which involves dataset preparation, designing classification model and evaluation. To facilitate experimentation image processing steps are followed, including image acquisition, image preprocessing (image filtering and attribute selection), image analysis (segmentation, feature extraction and classification), and image understanding for raw quality image scaling. ImageJ tool and Matlab programming language were used.