Kekarangan Balinese Carving Classification Using Gabor Convolutional Neural Network

I Putu Bagus Gede Prasetyo Raharja (Udayana University)
I Made Suwija Putra (Udayana University)
Tony Le (University of New Orleans)

Lontar Komputer: Jurnal Ilmiah Teknologi Informasi
Vol 13 No 1 (2022): Vol. 13, No. 1 April 2022

Balinese traditional carvings are Balinese culture that can easily be found on the island of Bali, starting from the decoration of Hindu temples and traditional Balinese houses. One of the types of Balinese traditional carving ornaments is Kekarangan ornament carving. Apart from the many traditional Balinese carvings, Balinese people only know the shape of the carving without knowing the name and characteristics of the carving itself. Lack of understanding in traditional Balinese carving is caused by the difficulty of finding sources of materials to study traditional Balinese carvings. A traditional Kekarangan Balinese carving classification system can help Balinese people to identify classes of traditional Balinese carving. This study used the Gabor CNN method. The Multi Orientation Gabor Filter is used in feature extraction and image augmentation, coupled with the Convolutional Neural Network method for image classification. The usage of the Gabor CNN method can produce the highest image classification accuracy of 89%.