Direct unsupervised text line extraction from colored historical manuscript images using DCT
المؤلف | Baig, Asim |
المؤلف | Al-Maadeed, Somaya |
المؤلف | Bouridane, Ahmed |
المؤلف | Cheriet, Mohamed |
تاريخ الإتاحة | 2021-09-07T06:16:17Z |
تاريخ النشر | 2016 |
اسم المنشور | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
المصدر | Scopus |
الرقم المعياري الدولي للكتاب | 3029743 |
الملخص | Extracting lines of text from a manuscript is an important preprocessing step in many digital paleography applications. These extracted lines play a fundamental part in the identification of the author and/or age of the manuscript. In this paper we present an unsupervised approach to text line extraction in historical manuscripts that can be applied directly to a color manuscript image. Each of the red, green and blue channels are processed separately by applying DCT on them individually. One of the key advantages of this approach is that it can be applied directly to the manuscript image without any preprocessing, training or tuning steps. Extensive testing on complex Arabic handwritten manuscripts shows the effectiveness of the proposed approach. Springer International Publishing Switzerland 2016. |
اللغة | en |
الناشر | Springer Verlag |
الموضوع | Color image processing DCT Historical manuscripts Segmentation Text line extraction |
النوع | Conference Paper |
الصفحات | 753-762 |
رقم المجلد | 9730 |
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