Image analysis – Applications – Personnel identification
Reexamination Certificate
2000-05-03
2003-05-13
Ahmed, Samir (Department: 2623)
Image analysis
Applications
Personnel identification
C392S488000, C340S005520
Reexamination Certificate
active
06563939
ABSTRACT:
BACKGROUND OF THE INVENTION
1. Field of the Invention
The present invention relates to a method of verifying an electronic signature. More particularly, the present invention relates to a method in which a degree of difference (cumulative error) between registered signature data and signature date to be verified is obtained during verification, and a signer is authenticated on the basis of the degree of difference, as well as to a method and apparatus for electronic-tablet correction.
2. Discussion of the Background
A handwritten character recognition method by which written characters are recognized has been utilized as an input method for word processors or a signature verification method for specifying a writer. Under a handwritten character recognition method which has already been in actual use as an input method, characters are input under specified constraints on the style of typeface (e.g., in the style of Kaisho in the case of Japanese), and the thus-input characters are converted into coordinate information. The thus-converted coordinate information is verified by comparison with coordinate information relating to character data which have been stored beforehand. As a result of verification, the characters are recognized as matched. If characters are carefully written in the kaisho style at comparatively slow speed in the manner as previously described, the characters can be sufficiently recognized through use of only coordinate information because under such conditions each of the strokes of the characters becomes clear by virtue of visual feedback to the writer and hence the shape of the characters becomes stable.
In contrast, in a case where the character recognition method is applied to an input method which does not pose any restriction on the style of typeface at the time of input of characters or to a signature verification method, there must be recognized not only characters written in the kaisho style but also cursively written characters. When characters are cursively written, writing motion becomes faster and does not involve any substantial visual feedback to the writer. In this case, the characters become less identifiable, and separation of a resultantly acquired pattern into strokes becomes difficult. Further, due to a large expansion or contraction of the pattern in the direction of the time axis or in the direction of stroke and/or the difference between the input pattern and a pre-registered pattern in these directions, a matching rate is extremely low, rendering recognition of characters difficult.
Another method is to enable recognition of characters without involving the separation of characters into strokes by application of time-series coordinate information and writing pressure. This method employs-a pattern matching technique called dynamic programming (DP) matching, which takes into consideration variations in the coordinate information stemming from variations in writing action.
In the DP matching technique, variations in the writing motion are corrected with regard to the time axis or the arc length axis through use of a skew function which minimizes a cumulative error between patterns to be checked. Patterns are matched with each other on the basis of the coordinates and writing pressure that have been corrected so as to compensate variations in the writing motion, thereby enabling recognition of cursively handwritten characters.
Verification based on the addition of writing-pressure information to time-series coordinate information or normalization of input patterns by DP matching contributes to an improvement in the recognition rate of handwritten characters. However, in the case of application of the DP matching technique to recognition of cursively written characters or signature verification, a false signature may be erroneously recognized as a genuine signature. Therefore, in its present form, the DP matching technique cannot be put into practical use.
Japanese Patent No. 1,822,532 [Japanese Patent Publication (kokoku) No. 5-31798] entitled “A Method of Recognizing Handwritten Characters Online” describes a practical technique that is based on DP matching. Under this method, when the degree of difference between a registered pattern and an input pattern of handwritten characters is calculated by use of DP matching, time-series coordinate information and writing-pressure information are simultaneously processed by the assignment of optimum weighting coefficients to the time-series coordinate information and writing-pressure information. As a result, the difference is reduced, which in turn contributes to an improvement in the verification rate of authenticity and a reduction in processing time.
As mentioned previously, even in the case of unclear characters which cannot be separated into strokes, processing of the time-series coordinate information and writing-pressure information relating to handwritten characters enables recognition of the characters. Further, even in the case of cursively handwritten characters, the characters can be recognized in practice, as a result of a further improvement in the DP matching technique that compensates variations in writing motion in order to correct cumulative errors.
In a static signature verification system, an image scanner or an image OCR is used as a tool for reading characters. In contrast, in a dynamic signature verification system, a stylus pen is generally used. An appearance of such a dynamic signature verification system utilizing a stylus pen is shown. When characters are written on a tablet through use of a stylus pen, signals representing characters are sent to a verification section, where signature verification is performed.
Such a tablet and stylus pen are important devices that affect easiness of use. Therefore, recently these devices have been improved. For example, a tablet formed from a liquid-crystal panel and a wireless stylus pen having no signal cable have come into use. Further, in place of a piece of hardware dedicated to signature verification, a personal computer has come into use. In this case, signature verification is performed by software.
The processing performed in the verification section is composed of three steps; i.e., pre-processing
ormalization, character extraction, and recognition/judgment. Information from the stylus pen includes relative coordinates (x, y) relative to the start point of a signature, and writing pressure p.
Since handwritten characters are not necessarily consistent, verification of a signature involves difficulty caused by variation in the direction of writing and in size, and hardware noise. The pre-processing
ormalization removes these variations and noise and performs normalization in order to enable comparison with standard character patterns. Specifically, in the pre-processing, there are performed removal of excess series of points (sampling based on amount of relative movement), removal of random noise that depends on hand shake and resolution of a tablet (smoothing through load shift), removal of isolated data caused by erroneous operation of the tablet, and like operations. After completion of such pre-processing, the size and position of input characters are normalized. Subsequent to the above-described processing, characteristics of the characters are extracted, and recognition/judgment processing is performed.
The above-described method for verifying electronic signatures is realistic and practical. However, such signature verification involves many drawbacks to be solved. One of the drawbacks is that a signature is not necessarily consistent.
Handwriting of a signature varies depending on the mental state of the person signing and the circumstances under which the person signs. How can we authenticate a person while absorbing such variations? How can we avoid a possibility that a third person whose imitates the handwriting of a certain person is authenticated as the certain person? These difficulties result in two types of errors in relation to signature verification; i.e., an error in which a c
Ahmed Samir
Cyber SIGN Japan Incorporated
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