Аннотация
A segmentation-free approach for off-line optical character recognition
is presented. The proposed method performs the recognition by extracting
the characters from the whole word, avoiding the segmentation process.
A control point set which includes position and attribute vectors
is selected for the features. In the training mode, each sample character
is mapped to a set of control points and is stored in an archive
which belongs to an alphabet. In the recognition mode, the control
points of the input image are first extracted. Then, each control
point is matched to the control points in the alphabet according
to its attributes. During the matching process, a probability matrix
is constructed which holds some matching measures (probabilities)
for identifying the characters. Experimental results indicate that
the proposed method is very robust in extracting the characters from
a cursive script
- (artificial
- algebra,
- archive,
- attribute
- character
- control
- cursive
- extraction
- extraction,
- feature
- group,
- image
- intelligence),
- learning
- matching
- matching,
- matrix
- matrix,
- measures,
- mode,
- off-line
- optical
- overlap
- point
- position
- probability
- probability,
- process,
- quality,
- recognition,
- script,
- segmentation-free
- set,
- training
- vectors,
- vectorsalphabet,
- word
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