This paper proposes a novel approach to extract distinctive keywords from historical newspaper images without using character recognition. We converted an image of the text block on an entire newspaper page into a sequence of codes based on discretization of the feature vectors, an approach that eliminated the errors introduced by optical character recognition (OCR). This conversion makes it possible to analyze untranscribed newspaper images by using text-processing methods. We examined the daily occurrence of every tri-gram string, and extracted strings with a dense appearance as distinctive keywords. In addition, we highlighted articles that contain distinctive keywords as distinctive articles. The proposed method was evaluated on an archive of Japanese newspaper images published in the 19th century, and the results were promising.
展开▼
