%0 Thesis
%9 Skripsi
%A ANDI FEBRIYANTO , NIM. 08650020
%B FAKULTAS SAINS DAN TEKNOLOGI
%D 2013
%F digilib:7218
%I UIN SUNAN KALIJAGA
%T ANALISIS KINERJA METODE BACKGROUND SUBTRACTION DAN  HAAR-LIKE FEATURE UNTUK MONITORING PEJALAN KAKI  MENGGUNAKAN KAMERA WEBCAM  
%U https://digilib.uin-suka.ac.id/id/eprint/7218/
%X The monitoring system is used to perform oversight functions for determining the  level of pedestrian crowds. To monitor pedestrians need to be created a system  that can detect and calculate the pedestrian crowds automatically. This research  will develop and compare two methods. Detection methods used are background  subtraction and haar like feature method. This research aim to determine the  performance of each method and compare the performance of both methods in  detecting pedestrians.  Background subtraction method can detect the subtraction in the background by  converting images into binary image and determines the sensitivity of  background's pixel changes. Haar like feature method uses 418 positive samples  and 644 negative samples as the data domain. The process of training carried out  on the samples which later became the basis for object detection pedestrians. Then  for both methods performed object detection and calculations processes.  From the test results of both methods with various test conditions, the detection  results using background subtraction method for pedestrian monitoring was  87.9%, while the result of detection using Haar-like feature method for pedestrian  monitoring was 65%. So the background subtraction method is better than Haarlike  Feature method for pedestrian monitoring.  Keywords : background subtraction, haar like feature, pedestrian detection