Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika
Vol 17, No 2 (2020): Komputasi: Jurnal Ilmiah Ilmu Komputer dan Matematika

ANALISIS PERBANDINGAN PELACAKAN OBJEK MENGGUNAKAN ALGORITMA HORN-SCHUNCK DAN LUCAS-KANADE

Wahyu Supriyatin (Gunadarma University)



Article Info

Publish Date
30 Jul 2020

Abstract

Computer vision same function as human eye, the ability to see or look objects passing by. Object tracking is one of computer vision. Object tracking aims is to recognize and identifying object pass and determine how many.This research was conducted by comparing the two algorithms in Optical Flow, the Horn-Schunck and the Lucas-Kanade algorithm. The test was carried out using two videos obtained from the Matlab library. The resolution of the video used in this study is same, 120x160. The camera used to pick up the objects in this study is placed in one position. The test is carried out using simulation parameters specified in each algorithm. Both algorithms successfully recognize and detect objects and can count how many objects are in a frame. In the same testing duration time simulation makes the Lucas-Kanade algorithm have a faster total record time than Horn-Schunck in recognizing and detecting of objects.

Copyrights © 2020






Journal Info

Abbrev

komputasi

Publisher

Subject

Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management

Description

Scientific Journal of Computer and Mathematical Science (Jurnal Ilmiah Ilmu Komputer dan Matematika) is initiated and organized by Department of Computer Science, Faculty of Mathematics and Science, Pakuan University (Unpak), Bogor, Indonesia to accommodate the writing of research results for the ...