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Oracle bone inscriptions is a kind of characters, which are i nscr bed on cattle bone or turtle shells with sharp objects about 3000 years ago. Understanding these inscript ions can give us a lot of insight into world history, character evaluations, global weather shifts, etc. Howeve r, for some political reasons the inscriptions remained buried in ruins until their discovery about 120 years ago. Th e aging process has caused the inscriptions to become less legible. In this work, we design a system and pr oposal a recognition method for recognizing oracle bone inscriptions as a template image from an oracle b on inscription database, by using the line feature of the inscriptions. First we use Gaussian filtering and labe ling to reduce noise and use affine transformation and thinning to extract the skeleton. Then we use Hough trans form to extracting the line feature points by proposing a method of clustering. Finally, we calculate the minimum distance of the line feature points between the original image and the template images to perfor m the recognition. Experimental results shows that almost 80% of inscriptions are recognized as the most mi nimum distance and the second-most minimumdistance. And the proposal can recognized well, even if the n oise and tilt happened in original images.

Recognition of Oracle Bone Inscriptions by Extracting Line Features on Image Processing