SEGMENTASI CITRA BERDASARKAN TEKSTUR MENGGUNAKAN PENGUKURAN LACUNARITY DENGAN METODE DIFFERENTIAL BOX-COUNTING

Abstract

This study aims to design and develop an application that can be used to segment the
image based on texture information using Lacunarity measurements. The method used in
calculating Lacunarity is Differential-Box Counting (DBC) method which was first
introduced by Dong (2000).
Implementation of Lacunarity-DBC method on this application produces an application
called "Lacunarity MAP" developed by using programming language Borland Delphi 7. This
application is only able to process RGB and Grayscale images with Bitmap format (*. BMP),
and produces output in the form of grayscale images. On the application of "Lacunarity
MAP" there are three main processes, among others : Lacunarity value calculation in any size
window, segmentation of Lacunarity values and edge detection. Testing is done by trying out
various kinds of images by entering a few parameters such as : box, window, and region.
These parameters which will affect the final outcome segmentation of the images. Based on
the results obtained that software testing "Lacunarity MAP" is able to provide maximum
results on several images to include the size of the box : 3,5,11 and 13, while the window
size: 6, 8, 10, 16, 20 and 22.