Advances In Handwriting RecognitionSeong-whan Lee World Scientific, 1999. gada 1. jūn. - 600 lappuses Advances in Handwriting Recognition contains selected key papers from the 6th International Workshop on Frontiers in Handwriting Recognition (IWFHR '98), held in Taejon, Korea from 12 to 14, August 1998. Most of the papers have been expanded or extensively revised to include helpful discussions, suggestions or comments made during the workshop. |
No grāmatas satura
1.5. rezultāts no 82.
4. lappuse
... combination or cooperation of several independent recognizers , the use of lexicons or dictionaries and of language models as post-processings have been suggested to improve the overall efficiency of the system. At the beginning of ...
... combination or cooperation of several independent recognizers , the use of lexicons or dictionaries and of language models as post-processings have been suggested to improve the overall efficiency of the system. At the beginning of ...
6. lappuse
... combined movements of the wrist and of the hand. This explains the fact that, for western handwriting, movements in the NE or SE directions are the easiest ones, that movements in the SW are a little bit more difficult and that ...
... combined movements of the wrist and of the hand. This explains the fact that, for western handwriting, movements in the NE or SE directions are the easiest ones, that movements in the SW are a little bit more difficult and that ...
7. lappuse
... Combination Rules These fundamental primitive shapes can also be based on a mathematical model, namely the curvature sign and its magnitude, the direction of the half-tangent and of the normal to the curve at the characteristic point(s) ...
... Combination Rules These fundamental primitive shapes can also be based on a mathematical model, namely the curvature sign and its magnitude, the direction of the half-tangent and of the normal to the curve at the characteristic point(s) ...
8. lappuse
... combination rules, a generic model of handwriting has been deduced *. 3.3 Fundamental Equation of Handwriting Based on several paleographic clues (the study of medevial texts, litterary author drafts, etc.) and on the basis of the ...
... combination rules, a generic model of handwriting has been deduced *. 3.3 Fundamental Equation of Handwriting Based on several paleographic clues (the study of medevial texts, litterary author drafts, etc.) and on the basis of the ...
9. lappuse
... combination of three activities: fisrt, perceiving the handwritten signs or some visual clues of the text (i.e. keystrokes, keyletters, keywords) second, using a lot of knowledge to finally reach a coherent interpretation of the text ...
... combination of three activities: fisrt, perceiving the handwritten signs or some visual clues of the text (i.e. keystrokes, keyletters, keywords) second, using a lot of knowledge to finally reach a coherent interpretation of the text ...
Saturs
17 | |
HANDWRITTEN FORM PROCESSING | 79 |
HANDWRITTEN WORD RECOGNITION | 151 |
SEGMENTATION | 223 |
ORIENTAL SCRIPT PROCESSING | 275 |
NUMERAL RECOGNITION | 357 |
EMERGING TECHNIQUES | 437 |
APPLICATIONS | 517 |
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algorithm applied approach B-spline bankcheck bigram character candidates character line character recognition character segmentation classifier combination computed connected components contour corresponding courtesy amount database described detected diacriticals dictionary digit distance error rate evaluation example experimental results experiments feature extraction feature set feature vectors Figure function fuzzy graph grapheme handwriting recognition handwritten character handwritten numerals handwritten words Hidden Markov Models horizontal Hough transform hypotheses integrated Kanji learning legal amount letters lexicon line segments matching matrix nat-ja neural network node obtained off-line on-line handwriting recognition optimal output paper parameters Pattern Recognition performance pixels points preprocessing probability problem Proc proposed method prototype quantization recognition rate recognition results recognition system recognizer samples sequence shown speech recognition step string stroke structure Suen Table technique template threshold touching type vector quantizer wavelet word recognition writing