Identifikasi Penyakit Tanaman Kubis Menggunakan Gaussian Filter dan Wavelet Transformation

Abstract

Decreased levels of cabbage production in Indonesia is caused by agricultural barriers such as diseases. Diseases on cabbage is difficult to identify. One solution that can be done is by using a digital image processing techniques. The use of digital image processing techniques is to facilitate the identification of cabbage diseases. This study uses Gaussian Filter and Wavelet Transformation to identify the type of cabbage diseases based on the image of its leaves. Gaussian filter method is applied to reduce noise in the image of diseased cabbage. Wavelet Transformation method is used as a feature extraction technique to the image. This study only focused on three types of cabbage diseases namely, leaf spot Alternaria, Black rot, and Downy mildew. In this study, identification of cabbage disease showed an accuracy of 85%. This suggests that the combination of these two methods can be applied to the identification of an image of cabbage diseases.