A large amount of handwritten historical documents are located in libraries around the world. The desire to access, search, and explore these documents paves the way for a new age of knowledge sharing and promotes collaboration and understanding between human societies. Currently, the indexes for these documents are generated manually, which is very tedious and time consuming. Results produced ...

The presence of handwritten text and annotations combined with typewritten machine-printed in historical archival records make them visually complex, posing challenges for OCR systems accurately transcribing their content. This paper is an extension [1], reporting on improvements the separation from (including typewriters), by use FCN-based models trained datasets created different data synthes...

text classification is an important research field in information retrieval and text mining. the main task in text classification is to assign text documents in predefined categories based on documents’ contents and labeled-training samples. since word detection is a difficult and time consuming task in persian language, bayesian text classifier is an appropriate approach to deal with different...

Given a set of handwritten documents, a common goal is to search for a relevant subset. Attempting to find a query word or image in such a set of documents is called word spotting. Spotting handwritten words in documents written in the Latin alphabet, and more recently in Arabic, has received considerable attention. One issue is generating candidate word regions on a page. Attempting to definit...

Nowadays, the accurate recognition of machine printed characters is considered largely a solved problem. A lot of commercial products are focused towards that direction, achieving high recognition rates. However, handwritten character recognition is comparatively difficult. So, the recognition of handwritten documents is still a subject of active research. In this thesis we studied the processi...