PENERAPAN METODE GABOR WAVELETS DAN MEDIAN FILTER UNTUK KLASIFIKASI POHON KELAPA SAWIT PADA DATA CITRA LIDAR - Sabila Rafani Aliandra, (2022)
The palm oil industry in Indonesia is demanded to be more productive and efficient. This study focuses on the problem of implementing algorithmic computational methods in digital image processing using machine learning technology that can be used as strategic tools in the process of maintaining and monitoring oil palm plantations. The purpose of this study was to determine the effectiveness of the application of the Median Filter and Gabor Wavelets method in classifying oil palm trees on LiDAR image data. A Median Filter that is able to remove salt and pepper noise in the image can help improve the quality of image clarity. Meanwhile, Gabor Wavelets which are very popular in digital image processing as a feature extraction method/texture features are expected to be able to select important features for the classification process. As a result, the Median Filter cannot significantly affect the classification results, because the image data does not contain a lot of salt and pepper noise. However, the image data processed by the Median Filter provides the highest accuracy and F1-score among other experiments in this study, which are 84.98% and 0.85093. On the other hand, Gabor Wavelets can affect the classification results, but still cannot improve accuracy and F1-score compared to the research.