Identifying join candidates in the Cairo Genizah

Lior Wolf, Rotem Littman, Naama Mayer, Tanya German, Nachum Dershowitz, Roni Shweka, Yaacov Choueka

Research output: Contribution to journalArticlepeer-review

Abstract

A join is a set of manuscript-fragments that are known to originate from the same original work. The Cairo Genizah is a collection containing approximately 350,000 fragments of mainly Jewish texts discovered in the late 19th century. The fragments are today spread out in libraries and private collections worldwide, and there is an ongoing effort to document and catalogue all extant fragments. The task of finding joins is currently conducted manually by experts, and presumably only a small fraction of the existing joins have been discovered. In this work, we study the problem of automatically finding candidate joins, so as to streamline the task. The proposed method is based on a combination of local descriptors and learning techniques. To evaluate the performance of various join-finding methods, without relying on the availability of human experts, we construct a benchmark dataset that is modeled on the Labeled Faces in the Wild benchmark for face recognition. Using this benchmark, we evaluate several alternative image representations and learning techniques. Finally, a set of newly-discovered join-candidates have been identified using our method and validated by a human expert.

Original languageEnglish
Pages (from-to)118-135
Number of pages18
JournalInternational Journal of Computer Vision
Volume94
Issue number1
DOIs
StatePublished - Aug 2011

Keywords

  • Cairo Genizah
  • Document analysis
  • Similarity learning

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