Affiliations: School of Mechanical and Electrical Engineering, Nanchang Institute of Technology, Nanchang, Jiangxi 330099, China
Correspondence:
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Corresponding author: Yongli Ma, School of Mechanical and Electrical Engineering, Nanchang Institute of Technology, Nanchang, Jiangxi 330099, China. E-mail: marymayl@126.com.
Abstract: This paper discusses the binarization restoration algorithms of ancient Chinese Rubbings image. According to the location of the image features, such as color, edge, stroke width and pixel location feature, the binary restoration algorithm of digital rubbings based on threshold segmentation and morphology is discussed. If the difference between the text and the background is larger and more obvious distinguish in images, Otsu threshold segmentation method can be directly used. For images with more background noise, shadows and uneven illumination, threshold segmentation cannot achieve effective segmentation and reasonable denoising, a set of algorithms associated with the pixel position of adaptive segmentation, morphological method, connected domain and mean filtering combined of binarization restoration are needed. The experimental results show that this algorithm is very effective for image with complex and large area noise.
