Word matching using single closed contours for indexing handwritten historical documents
نویسندگان
چکیده
منابع مشابه
Indexing of Handwritten Historical Documents - Recent Progress
Indexing and searching collections of handwritten archival documents and manuscripts has always been a challenge because handwriting recognizers do not perform well on such noisy documents. Given a collection of documents written by a single author (or a few authors), one can apply a technique called word spotting. The approach is to cluster word images based on their visual appearance, after s...
متن کاملConnected Component Based Word Spotting on Persian Handwritten image documents
Word spotting is to make searchable unindexed image documents by locating word/words in a doc-ument image, given a query word. This problem is challenging, mainly due to the large numberof word classes with very small inter-class and substantial intra-class distances. In this paper, asegmentation-based word spotting method is presented for multi-writer Persian handwritten doc-...
متن کاملOn the Influence of Word Representations for Handwritten Word Spotting in Historical Documents
Word spotting is the process of retrieving all instances of a queried keyword from a digital library of document images. In this paper we evaluate the performance of different word descriptors to assess the advantages and disadvantages of statistical and structural models in a framework of query-by-example word spotting in historical documents. We compare four word representation models, namely...
متن کاملText-image alignment for historical handwritten documents
We describe our work on text-image alignment in context of building a historical document retrieval system. We aim at aligning images of words in handwritten lines with their text transcriptions. The images of handwritten lines are automatically segmented from the scanned pages of historical documents and then manually transcribed. To train automatic routines to detect words in an image of hand...
متن کاملCITlab ARGUS for historical handwritten documents
We describe CITlab’s recognition system for the HTRtS competition attached to the 14. International Conference on Frontiers in Handwriting Recognition, ICFHR 2014. The task comprises the recognition of historical handwritten documents. The core algorithms of our system are based on multidimensional recurrent neural networks (MDRNN) and connectionist temporal classification (CTC). The software m...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Document Analysis and Recognition (IJDAR)
سال: 2006
ISSN: 1433-2833,1433-2825
DOI: 10.1007/s10032-006-0024-y