ANALISIS KINERJA METODE BACKGROUND SUBTRACTION DAN HAAR-LIKE FEATURE UNTUK MONITORING PEJALAN KAKI MENGGUNAKAN KAMERA WEBCAM

ANDI FEBRIYANTO , NIM. 08650020 (2013) ANALISIS KINERJA METODE BACKGROUND SUBTRACTION DAN HAAR-LIKE FEATURE UNTUK MONITORING PEJALAN KAKI MENGGUNAKAN KAMERA WEBCAM. Skripsi thesis, UIN SUNAN KALIJAGA.

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Abstract

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

Item Type: Thesis (Skripsi)
Subjects: Tehnik Informatika
Divisions: Fakultas Sains dan Teknologi > Teknik Informatika (S1)
Depositing User / Editor: Miftahul Ulum, S.Kom ------- youtube : ulum virgo -------- Facebook : digilibuin
Date Deposited: 18 Apr 2013 14:03
Last Modified: 07 Mar 2016 08:51
URI: http://digilib.uin-suka.ac.id/id/eprint/7218

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