Klasifikasi Kendaraan Menggunakan Gaussian Mixture Model (GMM) dan Fuzzy Cluster K Means (FCM)

Authors

  • Fitroh Amaluddin Program Magister Teknik Elektro Fakultas Teknik, Universitas Brawijaya
  • M. Aziz Muslim Jurusan Teknik Elektro Fakultas Teknik Universitas Brawijaya
  • Agus Naba Jurusan Teknik Elektro Fakultas Teknik Universitas Brawijaya

DOI:

https://doi.org/10.21776/jeeccis.v9i1.269

Abstract

This paper describes how to record a moving object and save as new video files (* .avi), then filtering the moving objects (Vehicles) by using a Gaussian Mixture Model (GMM) with 2 types of distribution, i.e. Bacground and Foreground distribution. The shape of the foreground distribution is filtered by morphological operations and segmented by using Bit Large Object (BLOB) Segmentation to get the vehicle dimensions. Feature extraction results of these vehicles, will be used as data cluster for vehicles classification by using Fuzzy Cluster Means (FCM). Resulting experiments show good results with 91.3% of accuracy rate.Index Terms—GMM, BLOB, FCM, Classification.

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How to Cite

[1]
F. Amaluddin, M. A. Muslim, and A. Naba, “Klasifikasi Kendaraan Menggunakan Gaussian Mixture Model (GMM) dan Fuzzy Cluster K Means (FCM)”, jeeccis, vol. 9, no. 1, pp. pp.19–24, Sep. 2015.

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