• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.6
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• pp.1345-1352
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• 2010

The structural approach in the signature verification, representing a signature as a structural form of local primitives, shows an excellent performance since it counts in the local characteristics such as local variation, stroke complexity, and etc. However, this method has a problem of template data sizing which can not fix the number of subpatterns comprising a signature. In this paper, we proposed a new algorithm to reduce the signature data into a fixed size by selecting a fixed number of subpatterns which is considered as important parts. As a result, it shows more excellent performance when the fixed sized sub-patterns is applied with local weights extracted from variational characteristics and complexities in local part. And the number of subpatterns representing a signature reference model can be fixed under a certain number of segments determined appropriately.

• Journal of Korea Multimedia Society
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• v.8 no.7
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• pp.961-973
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• 2005

In this paper, we proposed an adaptive steganography of color image using bit-planes and multichannel characteristics. Applying fixing threshold, if we insert information into all bit-planes of RGB channel, each channels showed different image quality. Therefore, we first defined the channel weight and the bit-plane weight to solve the fixing threshold problem of BPCS (bit-plane complexity steganography) method. We then proposed a new adaptive threshold method using the bit-plane weight of channels and the bit-plane complexity of cover image to increase insertion capacity adaptively In the experiment, we inserted information into the color images with the same image quality and same insertion capacity, and we analyzed the Insertion capacity and image quality. As a result, the proposed method increased the insertion capacity and improved the image quality than BPCS method.

• Journal of KIISE:Software and Applications
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• v.28 no.12
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• pp.875-884
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• 2001

Although the self organizing map (SOM) is widely utilized in such fields of data visualization and topology preserving mapping, since it should have the topology fixed before trained, it has some shortcomings that it is difficult to apply it to practical problems, and classification capability is quite low despite better clustering performance. To overcome these points this paper proposes the dynamic topology preserving self-organizing map(DTSOM) that dynamically splits the output nodes on the map and trains them, and attempts to improve the classification capability by combining multiple DTSOMs K-Winner method has been applied to combine DTSOMs which produces K outputs with winner node selection method. This produces even better performance than the conventional combining methods such as majority voting weighting, BKS Bayesian, Borda, Condorect and reliability sum. DTSOM remedies the shortcoming of determining the topology in advance, and the classification rate increases significantly by combing multiple maps trained with different features. Experimental results with handwritten digit recognition indicate that the proposed method works out to problems of conventional SOM effectively so to improve the classification rate to 98.1%.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2013.11a
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• pp.6-7
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• 2013

본 논문은 기존의 고정블록 알고리즘에서 발생할 수 있는 객체 추적의 문제점을 보안한 다중 블록을 이용한 적응적 블록 정합 알고리즘을 제안한다. 기존의 고정블록을 이용한 정합 알고리즘은 추적 대상 객체의 크기와 블록의 크기가 추적 성능에 미치는 영향이 크기 때문에 객체 추적에 실패하는 경우가 발생한다. 본 논문에서는 고정된 블록 정합 알고리즘의 문제점을 해결하기 위해 다중 블록을 이용하여 객체 내의 포함된 블록들을 효과적으로 선택하고 선택된 블록들의 특성으로부터 효과적인 가중치를 부여하여 추적 성능을 향상시킨다. 제안된 알고리즘은 블록 정합 알고리즘 중 가장 정확도가 높다고 알려진 전역 탐색 방법을 이용하여 정확도를 평가 하였다.

• The Transactions of the Korea Information Processing Society
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• v.6 no.6
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• pp.1563-1570
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• 1999

In this paper, we proposed the FPA(Fixed Partition Averaging) algorithm in order to improve the storage requirement and classification time of Memory Based Reasoning method. The proposed method enables us to use the storage more efficiently by extracting representatives out of training patterns. After partitioning the pattern space into a fixed number of equally-sized hyperrectangles, it averages patterns in each hyperrectangle to extract a representative. Also we have used the mutual information between the features and classes as weights for features to improve the classification performance.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.395-402
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• 2004

In this paper, we proposed a new method of the large capacity steganography using adaptive threshold on bit planes. Applying fixing threshold, if we insert information into all bit planes, all bit planes showed different image quality. Therefore, we first defined the bit plane weight to solve the fixing threshold problem. We then proposed a new adaptive threshold method using the bit plane weight and the average complexity to increase insertion capacity adaptively. In the experiment, we inserted information into the standard images with the same image quality and same insertion capacity, and we analyzed the insertion capacity and image duality. As a result, the proposed method increased the insertion capacity of about 6% and improved the image quality of about 24dB than fixed threshold method.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.328-330
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• 2015

Edge is a characteristic information that can easily obtain the size, direction and location of objects included in the image, and the edge detection is utilized as a preprocess processing in various image processing application sectors such as object detection and object recognition, etc. For the conventional edge detection methods, there are Sobel, Prewitt and Roberts. These existing edge detection methods are easy to implement but the edge detection characteristics are somewhat insufficient as fixed weighted mask is applied. Therefore, in order to compensate the problems of existing edge detection methods, in this paper, an edge detection algorithm was proposed after applying the weighted value according to the standard deviation and means within the local mask.

• The Transactions of the Korean Institute of Power Electronics
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• v.4 no.3
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• pp.223-230
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• 1999

A conventional sliding mode control approach is often impractical or difficult when it is applied to high order process b because the number of tuning parameters in the sliding mode controller increases with the order of the plant. C Camacho(l996) proposed a design method of a fixed structure sliding mode controller based on a first order plus dead t time approximation to the higher-order process. But, his method has such problems as chattering, over‘shoot, and c command following due to the Taylor the approximation en‘ors for the time delay term of the first order model. In this p paper, a new design technique for a sliding mode controller based on the modified Taylor approximation considered a w weight is developed to improve the Camacho's problems.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2015.10a
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• pp.420-423
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• 2015

This paper proposes a method of non-linearity error detection and calibration for binary-weighted charge-driven DACs. In general, the non-linearity errors of DACs often occur due to the mismatch of layout designs or process variation, even when careful layout design methods and process calibration are adopted. Since such errors can substantially degrade the SNDR performance of DAC, it is crucial to accurately measure the errors and calibrate the design mismatches. The proposed method employs 2 identical DAC circuits. The 2 DACs are sweeped, respectively, by using 2 digital input counters with a fixed difference. A comparator identifies any non-linearity errors larger than an acceptable discrepancy. We also propose a calibration method that can fine-tune the DAC's capacitor sizes iteratively until the comparator finds no further errors. Simulations are presented, which show that the proposed method is effective to detect the non-linearity errors and calibrate the capacitor mismatches of a 12-bit DAC design of binary-weighted charge-driven structure.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2975-2980
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• 2015

Edge detection is one of image processing techniques applied for a variety of purposes in a number of areas and it is used as a necessary pretreatment process in most applications. Detect this edge has been conducted in various fields at domestic and international. In the conventional edge detection methods, there are Sobel, Prewitt, Roberts and LoG, etc using a fixed weights mask. Since conventional edge detection methods apply the images to the fixed weights mask, the edge detection characteristics appear somewhat insufficient. Therefore in this study, to complement this, preprocessing using gray-level transformation function and algorithm finding final edge using maximum and minimum value of estimated mask by local mask are proposed. And in order to assess the performance of proposed algorithm, it was compared with a conventional Sobel, Roberts, Prewitt and LoG edge detection methods.