计算机科学
简单(哲学)
甲骨文公司
人工智能
分割
图像(数学)
图像分割
计算机视觉
卷积神经网络
程序设计语言
认识论
哲学
作者
Guoying Liu,Shanjia Xu,Wenying Ge,Hongyu Zhou,Jing Lv
摘要
Oracle bone inscriptions (OBIs) are invaluable materials for recovering the economic and social forms for Shang Dynasty, one of the most ancient dynasties in China. It is very important to get the original OBIs from scanned images of oracle bone rubbings. To this end, researchers have to employ a very time-consuming method that they follow the inscriptions by handwritten tools, pixel by pixel and image by image. In this paper, an image segmentation method was proposed to overcome this limitation based on fully convolutional networks (FCN). In order to speed up training as well as boost the segmentation performance, a simple FCN with only convolutional layers was designed, where batch normalization was incorporated. The proposed method was tested on a real OBI image set (320 samples). Experimental results show that the proposed method is effective enough to get the OBIs from scanned images of oracle bone rubbings.
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