KLASIFIKASI KATEGORI CITRA DIGITAL DENGAN METODE BAG OF VISUAL WORDS
Abstrak
Abstract: The human eye can distinguish objects from digital images, however, computers do not have the ability as human eyes that can directly distinguish objects from digital images. Therefore the bag of visual words method was created. Bag of visual words is a method for presenting digital images based on local features. Bag of visual words illustrates how an image can be taken its characteristics, so that computers can distinguish objects on digital images. The test results show that the bag of visual words are still not maximal in classifying digital image categories, especially the chair category, which is only able to produce the most accurate accuracy of 75%. To improve the performance quality of bag of visual words in classifying digital image categories, especially the chair category, you can add an approach to determine the good number of K in clustering the visual words pattern.
Keywords: Bag Of Visual Words, Classification, Digital Image, Speed-Up Robust Feature, Support Vector Machine
Abstrak: Secara kasat mata manusia bisa membedakan objek pada citra digital, namun, komputer tidak memiliki kemampuan sebagai mata manusia yang dapat secara langsung membedakan objek pada citra digital. Maka dari itu diciptakanlah metode bag of visual words. Bag of visual words adalah metode untuk menyajikan citra digital berdasarkan fitur lokal. Bag of visual words menggambarkan bagaimana suatu gambar dapat diambil karakteristiknya, sehingga komputer dapat membedakan objek pada citra digital. Hasil pengujian menunjukkan bag of visual words masih belum maksimal dalam mengklasifikasi kategori citra digital khususnya kategori chair, yang hanya mampu menghasilkan akurasi paling akurat sebesar 75 %. Untuk meningkatkan kualitas kinerja bag of visual words dalam mengklasifikasi kategori citra digital khususnya kategori chair, dapat menambahkan pendekatan untuk menentukan jumlah K yang baik dalam mengkluster pola visual words.
Kata kunci: Bag Of Visual Words, Klasifikasi, Citra Digital, Speed-Up Robust Feature, Support Vector Machine
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