A Framework for Efficient Transcription of Historical Documents Using Keyword Spotting
Konstantinos Zagoris, Ioannis Pratikakis, Basilis Gatos · 2015
Keyword spotting (KWS) has drawn the attention of the research community as the alternative means to solve hard cases of handwriting text recognition. In this paper, a framework is proposed that employs KWS to enhance the efficiency in the manual transcription process, thus, reducing drastically the cost of training data creation. The core principle relies upon the ability of robust document-specific descriptors to produce meaningful similarities between a chosen word image for transcription and the corresponding word images in the full dataset under consideration. In the proposed framework, KWS is coupled with a relevance feedback mechanism which further enhances retrieval performance while being independent to the chosen KWS algorithm. The efficiency of the proposed pipeline is showcased via a user-friendly web-based prototype.