IDENTIFICATION OF KOREAN HANGUL LETTERS IN HANDWRITTEN IMAGES USING THE K-NEAREST NEIGHBORS METHOD
Keywords:
Ginger Quality, Image Processing, K-Nearest Neighbor, Color And Texture.Abstract
Ginger plant is one of the rhizome plants that turns out to have properties and benefits for health, especially to increase immunity. However, many people do not know and it is difficult to distinguish the type of rhizome plant. This type of rhizome plant can be identified based on the characteristics seen from its color and texture. Therefore, an appropriate method is needed to determine the quality of ginger based on the color and texture to be studied, namely by using image processing technology which is expected to be able to improve the quality of ginger.
In this research stage, the first to collect references, input data, pre-processing, design, texture and color, testing, KNN, KNN testing, analysis, is completed, is a process to determine the stage to determine the quality value of ginger based on color and texture using RGB and GLCM.
Based on the results of research that has been done, namely fresh red ginger, with RGB values, Red 237,878 - 235,713, Green 234,745 - 232,193 and Blue 233,627 - 230,808. Withered red ginger, Red 247,029 – 245,232, Green 245,319 – 243,878, and Blue 244,243,878. fresh white ginger, valued at Red 242,836 – 234,169, Green 237.03 – 223,701, and Blue 232,418 – 215,035. White ginger withered, Red 243,604 – 235,871, Green 238,617-227,344, and Blue 234,307 – 219,862. As for the GLCM feature value obtained from 40 ginger testing data images, it is 97.5%.References
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