Identifikasi Landmark Ikonik Menggunakan Metode Histogram Of Oriented Gradient (hog) Dan Support Vector Machine (svm)

Muhammad Rakha, Dody Qori Utama, Ema Rachmawati

Abstract

Abstract
Identifikasi landmark oleh sistem sangat sulit dilakukan karena untuk mengidentifikasi sistem harus
mengenali ciri – ciri data dari citra tersebut, agar sistem dapat mengenali ciri - ciri citra landmark maka citra
tersebut harus di feature extraction dan dilakukan pembalajaran yang dijadikan kecerdasan buatan untuk
komputer. Indentifikasi Landmark Ikonik Menggunakan Metode Histogram of Oriented Gradient (HOG) dan
Support Vector Machine (SVM) merupakan sebuah sistem yang dapat mengidentifikasi objek landmark yang
ada pada citra dengan mengambil lapisan-lapisan seluruh citra gambar. Lapisan-lapisan citra di feature
extraction menggunakan metode Histogram of Oriented Gradient (HOG) kemudian lapisan-lapisan citra yang
di feature extraction dengan data training di klasifikasikan menggunakan Support Vector Machine (SVM)
sehingga sistem dapat mencari posisi dan mengidentifikasi nama landmark apa yang ada pada citra. Dari
hasil pengujian yang telah dilakukan mendapati bahwa identifikasi landmark ikonik menggunakan metode
Histogram of Oriented Gradient dan Support Vector Machine mendapatkan akurasi sebesar 84,4% kebenaran.
Kata kunci : support vector machine, histogram of oriented gradient, landmark, ikonik
Abstract:
Identification of landmarks by the system is very difficult to do because to identify the system, it must
recognize the data features of the image, so that the system can recognize the features of the landmark image,
the image must be feature extraction and a lesson made into artificial intelligence for the computer.
Identification of Iconic Landmarks Using the Histogram of Oriented Gradient (HOG) Method and Support
Vector Machine (SVM) is a system that can identify landmark objects in an image by taking the layers of the
entire image image. The image layers in feature extraction use the Histogram of Oriented Gradient (HOG)
method then the image layers that are feature extraction with training data are classified using a Support
Vector Machine (SVM) so that the system can search for positions and identify what landmark names are on
imagery. From the results of the tests that have been done, it is found that the identification of iconic landmark
using the Histogram of Oriented Gradient and Support Vector Machine method gets an accuracy of 84.4%.
Keywords: support vector machine, histogram of oriented gradient, landmark,iconic

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