US5633954A
Expired / Lapsed
US
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System and method for character recognition with normalization
Assignee: Massachusetts Institute of Technology
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Filing: 1994-09-30
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Granted: 1997-05-27
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Expires: 2014-09-30
Abstract
Abstract A character recognition system comprises means for receiving a first binary image of a plurality of characters; segmenting means for separating the first binary image into a plurality of second binary images corresponding to the plurality of characters in the first binary image; normalizing means for reducing variations among the characters, which normalizing means comprises stroke adjusting means for processing the second binary images to adjust strokes of the characters to a predetermined thickness, size normalization means for processing the second binary images to proportionally adjust the overall size of the characters to a predetermined overall size, and slant correction means for processing the second binary images to reduce a slant with respect to a predetermined axis of the characters; and recognizer means coupled to the normalizing means for processing the normalized second binary images to determine which character is represented by each of the normalized second binary images.
Inventors
- 👤 Amar Gupta
- 👤 Maram V. Nagendraprasad
- 👤 Patrick S. P. Wang
Bibliographic Details
Application Number
—
Jurisdiction
US
Data Source
google_patents
Last Synchronized
2026-11-09 17:43
CPC Classifications
G; G06; G06V; G06V30/00; G06V30/10; G06V30/14; G06V30/146; G06V30/1475; G06V30/1478; G06V30/16; G06V30/166; G06V30/19; G06V30/192; G06V30/194
Claims Analysis
Total Claims: 13
Claim 1
Independent Claim
203 words
A neural network-based character recognition system, comprising: a receiver for receiving a first binary image of a plurality of characters; a segmenter for separating the first binary image into a plurality of second binary images corresponding to the plurality of characters in the first binary image; a normalizer for reducing variations among the plurality of characters by processing the second binary images, comprising: a stroke adjuser for processing the second binary images to adjust strokes of the characters first to a one-pixel thickness and then to adjust the one-pixel thickness strokes to a second thickness which is substantially uniform and which is greater than the one-pixel thickness, a size normalizer for processing the second binary images to proportionally adjust the overall size of the characters to a predetermined overall size, and a slant correcter for processing the second binary images to reduce a slant with respect to a predetermined axis of the characters by using a binary search strategy which converges within a predetermined error margin; and a neural network recognizer coupled to the normalizer for processing the stroke-adjusted, size-normalized, and slant corrected second binary images to determine which character is represented by each of the second binary images processed by the normalizer.
Claim 2
Dependent Claim
203 words
A neural network-based character recognition system, comprising: a receiver for receiving a first binary image of a plurality of characters; a segmenter for separating the first binary image into a plurality of second binary images corresponding to the plurality of characters in the first binary image; a normalizer for reducing variations among the plurality of characters by processing the second binary images, comprising: a stroke adjuser for processing the second binary images to adjust strokes of the characters first to a one-pixel thickness and then to adjust the one-pixel thickness strokes to a second thickness which is substantially uniform and which is greater than the one-pixel thickness, a size normalizer for processing the second binary images to proportionally adjust the overall size of the characters to a predetermined overall size, and a slant correcter for processing the second binary images to reduce a slant with respect to a predetermined axis of the characters by using a binary search strategy which converges within a predetermined error margin; and a neural network recognizer coupled to the normalizer for processing the stroke-adjusted, size-normalized, and slant corrected second binary images to determine which character is represented by each of the second binary images processed by the normalizer.
Claim 3
Dependent Claim
27 words
The character recognition system of claim 1 further comprising a scanner for scanning a document having the plurality of characters thereon to create the first binary image.
Claim 4
Dependent Claim
14 words
The character recognition system of claim 2 wherein the document comprises a financial document.
Claim 5
Dependent Claim
14 words
The character recognition system of claim 3 wherein the financial document comprises a check.
Claim 6
Dependent Claim
17 words
The character recognition system of claim 1 wherein the plurality of characters comprises generally non-cursive, handwritten characters.
Claim 7
Dependent Claim
15 words
The character recognition system of claim 5 wherein the plurality of characters includes Arabic numerals.
Claim 8
Dependent Claim
31 words
The character recognition system of claim 1 wherein the neural network identifies one character from a predetermined set of characters for each of the second binary images processed by the normalizer.
Claim 9
Dependent Claim
42 words
The character recognition system of claim 7 wherein the neural network generates a confidence value for each of the characters identified from the predetermined set of characters to indicate a measure of the accuracy of the identification made by the neural network.
Claim 10
Dependent Claim
40 words
The character recognition system of claim 8 wherein the confidence value ranges from zero to one, a value of zero indicative of the worst possible accuracy of the identification and a value of one indicative of the best possible accuracy.
Claim 11
Dependent Claim
15 words
The character recognition system of claim 1 wherein the segmenter comprises a plurality of stages.
Claim 12
Independent Claim
145 words
A method of processing a binary image of a character and then providing the processed binary image to a neural network character recognizer for recognition by the neural network character recognizer as one of a predetermined set of characters, comprising the steps of: providing the binary image of the character which includes one or more strokes forming the character, each stroke having a length and a thickness which can vary over the length; processing the binary image to adjust each of the strokes of the character to a one-pixel thickness; processing the adjusted binary image to adjust each of the adjusted one-pixel thickness strokes of the character to a second thickness which is substantially uniform and which is greater than the one-pixel thickness; and providing the twice-adjusted binary image to the neural network character recognizer for recognition as one of the predetermined set of characters.
Claim 13
Independent Claim
145 words
A method of processing a binary image of a character and then providing the processed binary image to a neural network character recognizer for recognition by the neural network character recognizer as one of a predetermined set of characters, comprising the steps of: providing the binary image of the character which includes one or more strokes forming the character, each stroke having a length and a thickness which can vary over the length; processing the binary image to adjust each of the strokes of the character to a one-pixel thickness; processing the adjusted binary image to adjust each of the adjusted one-pixel thickness strokes of the character to a second thickness which is substantially uniform and which is greater than the one-pixel thickness; and providing the twice-adjusted binary image to the neural network character recognizer for recognition as one of the predetermined set of characters.
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USPTO Annuity & Maintenance Windows
| Annuity Stage | Window Opens | Payment Deadline | Surcharge Period Until | Estimated Fee | Status |
|---|---|---|---|---|---|
| 3.5 Years (Year 4) | 2000-05-26 | 2000-11-25 | 2001-05-27 | $2000.00 | Window Closed / Lapsed |
| 7.5 Years (Year 8) | 2004-05-26 | 2004-11-25 | 2005-05-27 | $3760.00 | Window Closed / Lapsed |
| 11.5 Years (Year 12) | 2008-05-26 | 2008-11-25 | 2009-05-27 | $7700.00 | Window Closed / Lapsed |