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Collector's seals provide important clues about the ownership of a book. Theycontain much information pertaining to the essential elements of ancientmaterials and also show the details of possession, its relation to the book,the identity of the collectors and their social status and wealth, amongstothers. Asian collectors have typically used artistic ancient characters ratherthan modern ones to make their seals. In addition to the owner's name, severalother words are used to express more profound meanings. A system thatautomatically recognizes these characters can help enthusiasts andprofessionals better understand the background information of these seals.However, there is a lack of training data and labelled images, as samples ofsome seals are scarce and most of them are degraded images. It is necessary tofind new ways to make full use of such scarce data. While these data areavailable online, they do not contain information on the characters'position.The goal of this research is to provide retrieval tools assist in obtainingmore information from Asian collector's seals imprints without consuming a lotof computational resources. In this paper, a character segmentation method isproposed to predict the candidate characters'area without any labelled trainingdata that contain character coordinate information. A retrieval-basedrecognition system that focuses on a single character is also proposed tosupport seal retrieval and matching. The experimental results demonstrate thatthe proposed character segmentation method performs well on Asian collector'sseals, with 92% of the test data being correctly segmented.

Character Segmentation in Asian Collector's Seal Imprints: An Attempt to Retrieval Based on Ancient Character Typeface