• Journal of the Korea Society for Simulation
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• v.14 no.3
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• pp.147-154
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• 2005

In conventional approaches such as a functinal approach or a parametric approach to online signature verification, which could not deal with the local shape of signature, much various important informations inherent in the local part of signature shape have been overlooked. In this paper, we try a structural approach in which a signature is represented as a structural form of handwriting primitives and the local parts along a signature handwriting can be selectively compared according to their discrimination power in the process of signature verification, As a result, the error rate is diminished in the case that the weights of subpattern units is applied into comparing process, which is the degree of discrimination power of local part. And also, the global variation and complexity of each signature extracted from the analysis of local shape is found useful in determining the decision threshold more precisely.

• The Transactions of the Korea Information Processing Society
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• v.5 no.11
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• pp.2884-2896
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• 1998

For on-line signature verification, the local shape of a signature is an important information. The current approaches, in which signatures are represented into a function of time or a feature vector without regarding of local shape, have not used the various features of local shapes, for example, local variation of a signer, local complexity of signature or local difficulty of forger, and etc. In this paper, we propose a new technique for on-line signature verification based on a structural signature representation so as to analyze local shape and to make a selection of important local parts in matching process. That is. based on a structural representation of signature, a technique of important of local weighting and personalized decision threshold is newly introduced and its experimental results under different conditions are compared.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.9
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• pp.1781-1785
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• 2007

We propose a new enhanced graphical user interface and algorithm for dynamic signature verification using Smart-phone. Also, we describe the performance results of our dynamic signature verification system, which determine the authentication of signatures by comparing and analyzing various dynamic data shape of the signature, writing speed, slant of shape, and the order and number of strokes for personal signatures using an electronic pen, expecting the system to be understood and utilized widely in the industrial field.

• 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.

• Computers and Concrete
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• v.7 no.6
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• pp.511-522
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• 2010

A color based segmentation procedure and a modified signature technique have been applied to the detection and analyses of complicated void shapes in cemented materials. The gray-scale segmentation and available signature methods were found to be inefficient especially for the analyses of complicated void shapes. The applicability of the developed methodology has been demonstrated on artificially prepared cemented materials made of self compacted concrete material. In order to characterize the void shapes in the investigated sample images, two new shape parameters called as coefficients of inclusion and exclusion have been proposed. When compared with the traditional use of the signature method, it was found that the methodology followed herein would better characterize complicated void shapes. The methodology followed in this study may be applied to the analysis of complicated void shapes that are often encountered in other cementitious materials such as clays and rocks.

• 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.

• Journal of the Korea Society of Computer and Information
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• v.16 no.11
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• pp.103-111
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• 2011

In this paper, we propose a Geometrical Centroid Contour Distance(GCCD) which is described by shape signature based on contour sequence. The proposed method uses geomertrical relation features instead of the absolute angle based features after it was normalized and aligned with dominant feature of the shape. Experimental result with MPEG-7 CE-Shape-1 Data Set reveals that our method has low time/spatial complexity and scale/rotation robustness than the other methods, showing that the precision of our method is more accurate than the conventional desctiptors. However, performance of the GCCD is limited with concave and complex shaped objects.

• 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.

• Convergence Security Journal
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• v.2 no.1
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• pp.35-47
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• 2002

In this paper, we will provide an overview of the motion picture watermarking techniques. We will see previously proposed algorithms such as compressed domain watermarking, non-compressed domain watermarking and algorithms for realtime applications etc. We will see test results for signature embedding in motion picture. By spread spectrum method, we embed a signature in each frames. The quality of watermarked motion picture is measured by PSNR(peak signal to noise ratio) about several strengths of watermark. In watermark detection the sign of the correlation sum is the estimated embedded signature bits. We will see different mean PSNR with visual shape of the detected signature.

• Journal of Korea Multimedia Society
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• v.3 no.6
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• pp.592-603
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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 it is genuine or forged with more than 98% overall accuracy even without any knowledge of varied freehand forgeries.