Ricardus Anggi Pramunendar
Universitas Dian Nuswantoro

Published : 17 Documents
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Journal : Jurnal Informatika Upgris

PENGEMBANGAN METODE PELACAKAN OBJEK BERBASIS SEGMENTASI MENGGUNAKAN ALGORITMA FCM prabowo, dwi puji; Pramunendar, Ricardus Anggi
Jurnal Informatika Upgris Vol 4, No 2: Desember (2018)
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (181.03 KB) | DOI: 10.26877/jiu.v4i2.2366

Abstract

Detection of object tracking is an important part of object recognition analysis. In object tracking applications, object detection is the first step of video surveillance, where accurate object detection becomes important and difficult because there are still problems that arise like the shadow of the detected object (false detection). To overcome this many object tracking applications are constantly being developed to produce accurate object detection. In this case the clustering method is one of the methods that are considered efficient and able to provide segmentation results in the image better and adaptive to changes in the environment and instantaneous changes quickly. So this research proposes the development of the object-oriented FCM method of object segmentation to obtain accurate object detection results. For the development of FCM method this research will be done by using distance approach. The distance approach used is cambera, chebychef, mahattan, minkowski, and Euclidean to get accurate results.
PELACAKAN DAN SEGMENTASI OBJEK BERGERAK MENGGUNAKAN METODE K-MEANS CLUSTERING BERBASIS VARIASI JARAK prabowo, dwi puji; latifah, khoiriya; Pramunendar, Ricardus Anggi
Jurnal Informatika Upgris Vol 5, No 1: Juni (2019)
Publisher : Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/jiu.v5i1.2818

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