ANALYSIS OF ADAPTIF LOCAL REGION IMPLEMENTATION ON LOCAL THRESHOLDING METHOD
I Gusti Agung Socrates Adi Guna, Hendra Maulana, Agus Zainal Arifin, Dini Adni Navastara · NJCA (Nusantara Journal of Computers and Its Applications) · 2017
Thresholding is a simple and effective technique for image segmentation. Thresholding techniques can be grouped into two categories, global thresholding and local thresholding. All local threshold method generally begins with determining thresholds in each pixel by checking the area centered on the pixel, using a box shape (x, y) which is fixed by the size of the neighborhood b. If the neighborhood is very small, then the algorithm will be sensitive to noise and excessive segmentation occurs. Whereas, if the size of the neighborhood is very large then the algorithm will apply resemble the global threshold method. In this study, we propose a method of calculation of Local Adaptive Region, to determine the value of each pixel that is flexible neighborhoods, where each pixel has values different neighborhoods based on the value of the standard deviation region. Adaptive method on the local region thresholding consists of several processes, namely: Image Enhancement, Adaptive Local Region and thresholding. Based on evaluation of ME, image result of threshold using the Adaptive Local Region method, giving an average ME smallest value, that is 16.99% at Niblack method and 19.46% at Sauvola method. And on evaluation of the RAE, image result of threshold using the Adaptive Local Region method, giving an average RAE smallest value, that is 15.26% at Niblack method and 25.58% at Sauvola method. In addition, the results of trials with various noise variance represent that the method of Adaptive Local Region resistant to noise.