Pengolahan Citra Digital Untuk Menghitung Ekstrasi Ciri Greenbean Kopi Robusta Dan Arabika (Studi Kasus: Kopi Temanggung) - Akhmad Fadjeri; Arief Setyanto; Mei P. Kurniawan (STMIK Sinar Nusantara, 2020)
This study aims to determine the extraction of features contained in robusta and arabica coffee greenbeans to make objects detectable and can be drawn into mathematical numbers. The method used is the original image which is converted to RGB and then grayscaling is carried out followed by a binary process that aims to change the image into binary form (0 and 1) after the digital image processing is complete the process of extracting the characteristics of greenbean coffee based on width, height, perimeter, surface area, roundness percentage, and perimeter of each coffee greenbean so that it can be understood mathematically. The results of the binary image process carried out morphological operations, the morphological process there is an erosion and dilation process. The results of the erosion and dilation process are carried out feature extraction to get the length, height, circumference, roundness ratio and perimeter of an image image. Then the value is stored in the database as a feature extraction of each greenbean coffee.The result of feature extraction obtained from coffee greenbean samples with a mean width of 7.7 pixels, height 11, circumference 31.3, surface area 69.5, roundness percentage 89,559, and perimeter 1,674 of greenbean robusta coffee while for arabica greenbean can be width 13.2 pixels, height 18.8, circumference 51.2, surface area 199.9, percentage of roundness 94.548, and perimeter 1.6000038 with total data taken were 20 greenbean coffees.