7. A method for identifying patterns by means of a pattern registration means and a data processing means, wherein each pattern comprises at least one unknown stroke generated by relative movement between a pattern-forming means and a pattern-accommodating means of said pattern registration means, said pattern registration means being operative to generate first signal information represented by first signals, said first signal information being representative of stroke information about said unknown stroke, said data processing means being provided with prestored second signal information represented by second signals, said second signal information including templates corresponding to template strokes, said data processing means being operative to generate third signals representing third signal information in response to said first signals and said second signals, said third signal information comprising identity labels for use in developing coded information which identifies said patterns, said method comprising: defining templates from said second signal information wherein at least one of said templates is a confusion group template, each said confusion group template being derived from information about at least two of said template strokes; generating distance metric values representative of closeness of stroke shape between said first signal information and said second signal information for at least each one of said confusion group templates; comparing said distance metric values of said unknown stroke for at least each confusion group template with an upper decision threshold value, with a lower decision threshold value and with a difference decision threshold value; and assigning a unique identity label corresponding to the template yielding the least distance metric value to the unknown stroke 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.
7. A method for identifying patterns by means of a pattern registration means and a data processing means, wherein each pattern comprises at least one unknown stroke generated by relative movement between a pattern-forming means and a pattern-accommodating means of said pattern registration means, said pattern registration means being operative to generate first signal information represented by first signals, said first signal information being representative of stroke information about said unknown stroke, said data processing means being provided with prestored second signal information represented by second signals, said second signal information including templates corresponding to template strokes, said data processing means being operative to generate third signals representing third signal information in response to said first signals and said second signals, said third signal information comprising identity labels for use in developing coded information which identifies said patterns, said method comprising: defining templates from said second signal information wherein at least one of said templates is a confusion group template, each said confusion group template being derived from information about at least two of said template strokes; generating distance metric values representative of closeness of stroke shape between said first signal information and said second signal information for at least each one of said confusion group templates; comparing said distance metric values of said unknown stroke for at least each confusion group template with an upper decision threshold value, with a lower decision threshold value and with a difference decision threshold value; and assigning a unique identity label corresponding to the template yielding the least distance metric value to the unknown stroke 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. 8. The method according to claim 7, wherein said assigning step includes assigning an identity label to said unknown stroke if the distance metric value which is least is less than the lower decision threshold value and if the next least distance metric value is greater than the upper decision threshold value.