Complex pattern recognition method and system
DCFirst Claim
1. A method for identifying patterns by means of a pattern registration means and a data processing means, wherein each pattern comprises at least one stroke based upon relative movement between a pattern-forming means and a pattern-accommodating means of said registration means, said registration means being operative to generate first signal information represented by first signals specifying relative position sequentially along a stroke, said data processing means being provided with prestored second signal information represented by second signals and being operative to generate third signals representing third signal information, said third signal information comprising specification of identity labels for strokes for use in developing coded information specifying said pattern, said method comprising for at least one stroke:
- designating from said first signal information a set of sequential first data points, said set of first data points being selected from or interpolated on the basis of said first signal information along said stroke;
defining templates consisting of said second signal information, each said template comprising a set of second data points defining relative sequentially related position values and a set of permissible tolerance values, each of said tolerance values representing a preselected deviation for its associated second data point, at least one of said permissible tolerance values differing from at least one other of said permissible tolerance values for a single template; and
comparing said first data points with said second data points to determine which of said templates provides best correspondence between said first and second signal information to produce said third signal information.
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Abstract
A method and system for recognizing complex patterns, such as Chinese characters (or Kanji), identifies patterns by stroke recognition using detailed information about stroke shape and specifically curvature characteristics. Written strokes are categorized into different specific stroke types and are assigned stroke identity labels by comparison of distance metrics generated with reference to stroke templates, each template comprising information specifying position of a point and permissible deviation for each such point along a stroke. Deviation values may differ from point to point and from stroke type to stroke type. The data on the written stroke may be rotated or displaced relative to each stroke template to enhance the likelihood of stroke recognition. Limited information about stroke position relative to other strokes may be preserved and employed to resolve ambiguities among accumulations of stroke identity labels found to ambiguously indicate more than one pattern or character.
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Citations
42 Claims
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1. A method for identifying patterns by means of a pattern registration means and a data processing means, wherein each pattern comprises at least one stroke based upon relative movement between a pattern-forming means and a pattern-accommodating means of said registration means, said registration means being operative to generate first signal information represented by first signals specifying relative position sequentially along a stroke, said data processing means being provided with prestored second signal information represented by second signals and being operative to generate third signals representing third signal information, said third signal information comprising specification of identity labels for strokes for use in developing coded information specifying said pattern, said method comprising for at least one stroke:
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designating from said first signal information a set of sequential first data points, said set of first data points being selected from or interpolated on the basis of said first signal information along said stroke; defining templates consisting of said second signal information, each said template comprising a set of second data points defining relative sequentially related position values and a set of permissible tolerance values, each of said tolerance values representing a preselected deviation for its associated second data point, at least one of said permissible tolerance values differing from at least one other of said permissible tolerance values for a single template; and comparing said first data points with said second data points to determine which of said templates provides best correspondence between said first and second signal information to produce said third signal information. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26)
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27. In an apparatus for identifying patterns by means of a pattern registration means and a data processing means, wherein each pattern comprises at least one stroke based on relative movement between a pattern-forming means and a pattern-accommodating means of said stroke registration means, said stroke registration means being operative to generate first signal information represented by first signals specifying relative position sequentially along a stroke, said data processing means being provided with prestored second signals and being operative to generate third signals representing third signal information, said third signal information comprising specification of identity labels for strokes for use in developing coded information specifying said pattern, the improvement characterized in that:
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said data processing means includes means for designating from said first signal information a set of sequential first data points, said set of first data points being selected from or interpolated on the basis of said first signal information, along said stroke means defining templates consisting of said second signal information, each said template comprising a set of second data points defining relative sequential position values and set of permissible tolerance values, each of said tolerance values representing a preselected deviation for its associated second data point, at least one of said permissible tolerance values differing from at least one other of said permissible tolerance values for a single template; and means for comparing said first data points with said second data points to determine which of said templates provides best correspondence between said first and second signal information to produce said third signal information. - View Dependent Claims (28, 29, 30, 31, 32, 33, 34, 35, 36)
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37. A method for identifying patterns by means of a pattern registration means and a data processing means, wherein each pattern comprises at least one stroke based upon relative movement between a pattern-forming means and a pattern-accommodating means of said registration means, said registration means being operative to generate first signal information represented by first signals specifying relative position sequentially along a stroke, said data processing means being provided with prestored second signal information represented by second signals and being operative to generate third signals representing third signal information, said third signal information comprising specification of identity labels for strokes for use in developing coded information specifying said pattern, said method comprising for at least one stroke:
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designating from said first signal information a set of first data points on the basis of said first signal information along said stroke; defining templates consisting of said second signal information, each said template comprising a set of second data points defining at least relative sequentially related position values; comparing said first data points with said second data points by computing the closeness between each one of said first data points and said second data points to obtain a distance metric value for each of said templates, thereafter comparing said distance metric value for each said template with an upper decision threshold, with a lower decision threshold and with a difference threshold and assigning a specific identity label of one of said predefined template strokes as said third signal information if the least distance metric value is less than the upper decision threshold value and if the next least distance metric value is greater than the sum of the least distance metric value and the difference decision threshold value. - View Dependent Claims (38, 39, 40, 41, 42)
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Specification