Jurnal Informatika Upgris
Vol 5, No 1: Juni (2019)

PELACAKAN DAN SEGMENTASI OBJEK BERGERAK MENGGUNAKAN METODE K-MEANS CLUSTERING BERBASIS VARIASI JARAK

prabowo, dwi puji (Unknown)
latifah, khoiriya (Unknown)
Pramunendar, Ricardus Anggi (Unknown)



Article Info

Publish Date
01 Jul 2019

Abstract

In computer vision tracking and object segmentation is one important step in video processing. Accuracy in object tracking is important in video processing, where accurate object tracking is a thing that continues to be done by many researchers. there are still many problems that are often experienced when tracking objects in terms of lighting, noise up to a high level of error. Many methods can be used in research, one of which is clustering method. Clustering method is a method that is widely used in grouping data, one of which is often used is Kmeans clustering. This method is very flexible, and is able to classify large amounts of data. Besides that, Kmeans is also able to work adeptly and segment the image well. For this study using 5 distance approaches (cambera, chebychef, mahattan, minkowski, Euclidean) distance approach which is expected to improve the results of better accuracy. From the results of the research produced a mahatan distance approach has the best accuracy results with a PNSR value of 16,34399 and the lowest MSE value with a value of 1521,793. Compared to the use of standard models with Euclidean, the approach of high distance accuracy increases

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Journal Info

Abbrev

JIU

Publisher

Subject

Computer Science & IT

Description

Journal of Informatics UPGRIS published since June 2015 with frequency 2 (two) times a year, ie in June and December. The editors receive scientific writings from lecturers, teachers and educational observers about the results of research, scientific studies and analysis and problem solving closely ...