Khmer Calligraphy Style Transfer Using SkelGAN
Chanarin Heng, Worasait Suwannik · 2023
Font style transfer is a challenging task in computer vision, aimed at extracting the visual characteristics such as stroke contrast and apply them to the content image. In this article, we focus on utilizing SkelGAN, a modified version of the U-Net architecture, to transfer font styles from English to Khmer characters. For our experiment, we collected a dataset of 15 calligraphy fonts containing both Khmer and English characters. To assess the performance of the generated images, we used the Structural Similarity Index Measure (SSIM). We compare the generated images with the ground truth images, providing a quantitative assessment of their similarity. Our experimental results indicate that SkelGAN successfully performs style transfer from English calligraphy to Khmer calligraphy, achieving an average SSIM score of 0.93. This score signifies a significant resemblance between the generated and target styles.