• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.2
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• pp.229-236
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• 2005

This paper is contribute to Inverse continuous wavelets transform(ICWT) which permits to determine real 'time-scale' plan. The application of ICWT is not yet represented because of the numerical difficulty. If the signal can be reconstructed stably by ICWT, the multi scale filter bank system which composed by analysis and synthesis process can be designed. In this work, we represent the ICWT which leads to nearly perfect reconstruction of signal and the multi-scale filter bank system.

• Journal of Korean Society for Geospatial Information Science
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• v.18 no.4
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• pp.101-107
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• 2010

The aim of this paper is to come up with a methodology of constructing an efficient model for multiple representations which can manage and reconcile real-time data about large-scale roads in Vector Domain. In other words, we suggested framework based on a bottom-up approach, which is allowed to integrate data from the network of the lowest level sequentially and perform automated matching in order to produce variable-scale map. Finally, we applied designed multi-LoD model to in-vehicle application.

• Journal of Information Processing Systems
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• v.16 no.5
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• pp.1083-1094
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• 2020

Recognizing plant species based on leaf images is challenging because of the large inter-class variation and inter-class similarities among different plant species. The effective extraction of leaf descriptors constitutes the most important problem in plant leaf recognition. In this paper, a multi-scale angular description method is proposed for fast and accurate leaf recognition and retrieval tasks. The proposed method uses a novel scale-generation rule to develop an angular description of leaf contours. It is parameter-free and can capture leaf features from coarse to fine at multiple scales. A fast Fourier transform is used to make the descriptor compact and is effective in matching samples. Both support vector machine and k-nearest neighbors are used to classify leaves. Leaf recognition and retrieval experiments were conducted on three challenging datasets, namely Swedish leaf, Flavia leaf, and ImageCLEF2012 leaf. The results are evaluated with the widely used standard metrics and compared with several state-of-the-art methods. The results and comparisons show that the proposed method not only requires a low computational time, but also achieves good recognition and retrieval accuracies on challenging datasets.

• IEMEK Journal of Embedded Systems and Applications
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• v.12 no.4
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• pp.231-238
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• 2017

Detecting small infrared targets from the low-SCR images at a long distance is very hard. The previous Local Contrast Method (LCM) algorithm based on the human visual system shows a superior performance of detecting small targets by a background suppression technique through local contrast measure. However, its slow processing speed due to the heavy multi-scale processing overhead is not suitable to a variety of real-time applications. This paper presents a lightweight real-time small target detection algorithm, called by the Improved Selective Local Contrast Method (ISLCM), to reduce the scale-invariant computational overhead. The proposed ISLCM applies the improved local contrast measure to the predicted selective region so that it may have a comparable detection performance as the previous LCM while guaranteeing low scale-invariant computational load by exploiting both adaptive scale estimation and small target feature feasibility. Experimental results show that the proposed algorithm can reduce its computational overhead considerably while maintaining its detection performance compared with the previous LCM.

• Proceeding of EDISON Challenge
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• 2015.03a
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• pp.138-146
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• 2015

액체 상태의 물질이 매우 급속하게 냉각되면 일반적으로 과냉각액체(supercooled liquid) 상태에 도달한다. 과냉각액체는 더 낮은 온도에서 유리상(glass phase)으로 상전이를 일으킨다고 알려져 있는데, 이때 나타나는 동역학적 불균일성(dynamic heterogeneity)은 상전이를 기술하는데 중요한 역할을 한다. 그러나 일반적인 액체의 상전이를 연구할 때 주로 사용되던 상관함수(correlation function)으로는 이러한 불균일성을 정량적으로 표현하기 어렵기 때문에 동역학적 민감도(dynamic susceptibility)나 multi-time correlation function 등 동역학적 성질(dynamic property)로부터 특징적인 시간 개념 및 거리 개념을 도출하려는 연구가 많이 진행되어 왔다. 본 논문에서는 일반적으로 특징적인 거리 개념을 도출해 내는데 사용되는 4점 밀도 상관함수(four-point density correlation function)인 dynamic susceptibility(${\chi}^4$)가 입자 밀도의 요동(fluctuation)의 상관관계(correlation)가 지속되는 특징적인 시간 개념에 대한 정보 또한 포함하고 있다는 점에 주목하였다. 이에 따라 ${\chi}^4$의 시간에 대한 적분인 ${\tau}_4$를 새롭게 도입하였으며 그 결과로 ${\tau}_4$는 three-time density correlation function으로부터 도출한 ${\tau}_{Dh}$와 같은 축척(scaling)을 가지는 것을 확인하였다. 과냉각액체에 대한 장난감 모형(toy model)의 일종인 "Lennard-Jones potential 하에서 운동하는 서로 다른 두 종류의 입자들"을 연구에 사용하였다.

• Proceedings of the Acoustical Society of Korea Conference
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• 1991.06a
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• pp.58-63
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• 1991

This paper describes development of small scale voice dialing system using TMS320C30. Recognition vocabuliary is used 50 department name within university. In vocabulary below the middle scale, word unit recognition is more practice than phoneme unit or syllable unit recognition. In this paper, we performend recognition and model generation using DMS(Dynamic Multi-Section) and implemeted voice dialing system using TMS320C30. As a result of recognition, we achieved a 98% recognition rate in condition of section 22 and weight 0.6 and recognition time took 4 seconds.

• Journal of Institute of Control, Robotics and Systems
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• v.19 no.11
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• pp.968-973
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• 2013

In the transportation industry, especially in the shipbuilding process, 3D surface measurement of large-scale hull pieces is needed for fabrication and assembly. We suggest an efficient method for checking the shape of curved plates under the forming operation with short time by measuring 3D profiles along the multi lines of the target surface. For accurate profile reconstruction, 2D camera calibration and 3D calibration using gauge blocks were performed. The evaluation test shows that the measurement accuracy is within the boundary of tolerance required in the shipbuilding process.

• Journal of the Korean Society for Railway
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• v.4 no.2
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• pp.47-54
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• 2001

Railway companies have been faced with many changes in the railway environment. To cope immediately with the influence of environment and to improve productivity, an efficient train operation system and related core technologies must be introduced. The railway system is composed of large scale infrastructures and high-cost trains. Simulation method is one of core technologies and also efficient tool for planning and analyzing these kinds of complex system. In this research, we review basic simulation programming models and present a modeling for the elements of railway system such as rail-line infrastructure, train, time table and operational route. Additionally, some considerations on the development of multi-train traffic simulator for KyongBu-line are discussed.

• Journal of Information Processing Systems
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• v.13 no.6
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• pp.1628-1639
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• 2017

The combination texture feature extraction approach for texture image retrieval is proposed in this paper. Two kinds of low level texture features were combined in the approach. One of them was extracted from singular value decomposition (SVD) based dual-tree complex wavelet transform (DTCWT) coefficients, and the other one was extracted from multi-scale local binary patterns (LBPs). The fusion features of SVD based multi-directional wavelet features and multi-scale LBP features have short dimensions of feature vector. The comparing experiments are conducted on Brodatz and Vistex datasets. According to the experimental results, the proposed method has a relatively better performance in aspect of retrieval accuracy and time complexity upon the existing methods.

• Phonetics and Speech Sciences
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• v.11 no.4
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• pp.89-96
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• 2019

In this paper, we propose a deep learning architecture that can effectively detect speech segmentation in broadcast contents. We also propose a multi-scale time-dilated layer for learning the temporal changes of feature vectors. We implement several comparison models to verify the performance of proposed model and calculated the frame-by-frame F-score, precision, and recall. Both the proposed model and the comparison model are trained with the same training data, and we train the model using 32 hours of Korean broadcast data which is composed of various genres (drama, news, documentary, and so on). Our proposed model shows the best performance with F-score 91.7% in Korean broadcast data. The British and Spanish broadcast data also show the highest performance with F-score 87.9% and 92.6%. As a result, our proposed model can contribute to the improvement of performance of speech detection by learning the temporal changes of the feature vectors.