Abstract

This paper introduces Oracle Bone Inscription Detector which based on Single Shot Multibox Detector, for segmenting and recognizing Oracle Bone Inscriptions from rubbing images. Oracle Bone Inscription which is the one of the oldest and most mysterious ancient characters, used about 3000 years ago in china, and lots of these literature are stored by rubbing images. Because that only few of specialists understand the Oracle Bone Inscriptions, lots of Oracle Bone Inscriptions are waiting for be understood for helping researchers know the history, culture, economy etc. Currently, deep learning method of single shot multibox detector achieves a good performance for segmentation and recognition, and may achieve a good performance for Oracle Bone Inscription detection. However, we fond the Single Shot Multibox Detector is weak at small object detection. This research equips and extends Single Shot Multibox Detector for Oracle Bone Inscription detection, and analyzes the mis-detection for achieving a better accuracy. The experimental results shows that Precision, Recall and F value achieve 0.95, 0.83 and 0.88 respectively, and proves the effectiveness of extended Single Shot Multibox Detector in Oracle Bone Inscription detection.

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