• Journal of KIISE:Software and Applications
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• v.34 no.12
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• pp.1065-1074
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• 2007

Among various methods to compare reference signatures with an input signature, the segment-to-segment matching method has more advantages than global and point-to-point methods. However, the segment-to-segment matching method has the problem of having lower recognition rate according to the variation of partitioning points. To resolve this drawback, this paper proposes a signature verification method by considering linear discriminant analysis as well as segment-to-segment matching method. For the final decision step, we adopt statistical based Bayesian classifier technique to effectively combine two individual systems. Under the various experiments, the proposed method shows better performance than segment-to-segment based matching method.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.4 no.2
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• pp.87-95
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• 2003

Dynamic Programming Matching (DPM) is a mathematical optimization technique for sequentially structured problems, which has, over the years, played a major role in providing primary algorithms in pattern recognition fields. Most practical applications of this method in signature verification have been based on the practical implementational version proposed by Sakoe and Chiba [9], and il usually applied as a case of slope constraint p = 0. We found, in this case, a modified version of DPM by applying a heuristic (forward seeking) implementation is more efficient, offering significantly reduced processing complexity as well as slightly improved verification performance.

• The KIPS Transactions:PartB
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• v.10B no.4
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• pp.451-458
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• 2003

Dynamic Programming Matching (DPM) is a mathematical optimization technique for sequentially structured problems, which has, over the years, played a major role in providing primary algorithms in pattern recognition fields. Most practical applications of this method in signature verification have been based on the practical implementational version proposed by Sakoe and Chiba [9], and is usually applied as a case of slope constraint p = 0. We found, in this case, a modified version of DPM by applying a heuristic (forward seeking) implementation is more efficient, offering significantly reduced processing complexity as well as slightly improved verification performance.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.3
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• pp.129-137
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• 2004

This paper presents a signature verification method that uses Gabor filter in computing similarity between signatures. In computing similarity to compare two on-line signatures, the temporal relationship between two signatures should be computed in advance. However, conventional point matching method using DP(dynamic programming) matching consumes much computation. In this paper, we propose a fast method for computing the temporal relationship between two on-line signatures by using the phase output of Gabor Inter applied on the on-line signature signals. Two similarity measures are defined in the method: Temporal Similarity and Temporally Arranged Feature Profile Similarity. With the proposed method, Ive could compare signatures 30 times faster than conventional method using DP matching.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.4
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• pp.890-895
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• 2005

Dynamic (On-line) signature verification system consists of preprocessing, feature extraction, comparison and decision process for internal processing, and registration and verification windows for the user interface. We describe an implementation and design for an advanced dynamic signature verification system. Also, we suggest the method of feature extraction, matching algorithm, efficient user interface and an objective criteria for evaluating the performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.5 no.4
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• pp.33-40
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• 1995

This paper delas with the detection of freehand forgeries of signatures based on the averaged directional amplitudes of gradient vetor which are related to the overall shape of the handwritten signature and fuzzy ARTMAP neural network classifier. In the first step, signature images are extracted from the background by a process involving noise reduction and automatic thresholding. Next, twelve directional amplitudes of gradient vector for each pixel on the signature line are measure and averaged through the entire signature image. With these twelve averaged directional gradient amplitudes, the fuzzy ARTMAP neural network is trained and tested for the detection of freehand forgeries of singatures. The experimental results show that the fuzzy ARTMAP neural network cna lcassify a signature whether genuine or forged with greater than 95% overall accuracy.

• Proceedings of the Korea Multimedia Society Conference
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• 2000.11a
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• pp.250-255
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• 2000

This paper is concerning off-line signature verification using a density function which is obtained by convolving the signature image with twelve-directional 5$\times$5 gradient masks and the weighted fuzzy mean classifier. The twelve-directional density function based on Nevatia-Babu template gradient is related to the overall shape of a signature image and thus, utilized as a feature set. The weighted fuzzy mean classifier with the reference feature vectors extracted from only genuine signature samples is evaluated for the verification of freehand forgeries. The experimental results show that the proposed system can classify a signature whether genuine or forged with more than 98% overall accuracy even without any knowledge of vaned freehand forgeries.

• Journal of Intelligence and Information Systems
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• v.7 no.2
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• pp.143-151
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• 2001

This paper investigates the development of a neural network based system for automated signature authentication that relies on an autoregressive characterization for the segments of a signature. The primary contributions of this work are tow-fold: a) the development of the neural network architecture and the modalities of training it, b) adaptation of the dynamic time warping algorithm to fomulate a new method for enabling consistent segmentation of multiple signatures from the same writer. The performance of the signature verification system has been tested using a sizable database that includes a comprehensive set of simulated and realistic forgeries. False Acceptance and False Rejection error rates of 0.78% and 1.6% respectively were obtained in tests conducted using 1920 skilled forgeries.

• Journal of the Korea Society of Computer and Information
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• v.10 no.4 s.36
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• pp.385-396
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• 2005

In this paper, a new structural approach to on-line signature verification is presented. A primitive pattern is defined as a part segmented by a local minimal position of speed. And a structural description of signature is composed of subpatterns which are defined as such forms as rotation shape, cusp shape and bell shape, acquired by composition of the primitives regarding the directional changes. As the matching method to find identical parts between two signatures, a modified DP(dynamic programming) matching algorithm is presented. And also, variation and complexity of local parts are computed from the training samples, and reference model and decision boundary are derived from these. Error rate, execution time and memory usage are compared among the functional approach, the parametric approach and the proposed structural approach. It is found that the average error rate can be reduced from 14.2% to 4.05% when the local parts of a signature are weighted and the complexity is used as a factor of decision threshold. Though the error rate is similar to that of functional approaches. time consumption and memory usage of the proposed structural approach are shown to be very effective.

• Proceedings of the Korea Inteligent Information System Society Conference
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• 2001.06a
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• pp.137-147
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• 2001