Handwritten Balinese Script Recognition on Palm Leaf Manuscript using Projection Profile and K-Nearest Neighbor

Abstract

This paper presents a simple approach to the handwritten Balinese script characters recognition in palm-leaf lontar manuscripts. The Lontar manuscript is one of the cultural heritages found in Bali. Lontar manuscripts are written using a pengrupak, which is a kind of knife for writing on palm leaves. To give color to the results of the writing, candlenut is used so that the writing appears clear. In this paper, we apply the projection profile at the segmentation stage to get the handwritten Balinese script characters in the lontar manuscript. The palm leaf manuscript that we use is the Wariga Palalubangan palm leaf. The recognition process is carried out by implementing K-Nearest Neighbor in the recognition process. The recognition was made on the Wianjana script obtained from lontar manuscripts using 720 images consisting of 18 classes as dataset training. The test results showed that the level of recognition accuracy was obtained by 52% in the characters of handwritten Balinese scripts derived from lontar manuscripts and 92% in the characters of handwritten Balinese scripts on paper.