• The Journal of the Korea Contents Association
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• v.2 no.4
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• pp.46-50
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• 2002

This paper suggests the adaptive binary method which applies advanced silt sum technique, so that threshold value can be changed heuristically according to the brightness of captured fingerprint image. Through this research, we tried to resolve threshold value setting issue by the local differences of brightness of fingerprint image in the binary image preprocessing. The experimental results show that our proposed preprocessing method demonstrates the better recognition accuracy and can be applied to minutiae extraction algorithm for fingerprint recognition system.

• Journal of Korea Society of Industrial Information Systems
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• v.22 no.6
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• pp.39-45
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• 2017

Conventional Color-Based Face Recognition Methods are Sensitive to Illumination Changes, and there are the Possibilities of Forgery and Falsification so that it is Difficult to Apply to Various Industrial Fields. In This Paper, we propose a Face Recognition Method Based on LBP(Local Binary Pattern) using the Depth Images to Solve This Problem. Face Detection Method Using Depth Information and Feature Extraction and Matching Methods for Face Recognition are implemented, the Simulation Results show the Recognition Performance of the Proposed Method.

• Journal of the Korean Institute of Intelligent Systems
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• v.12 no.3
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• pp.227-230
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• 2002

An important preprocessing for fingerprint recognition is the binarization operation, which takes as an input gray-scale image and returns a binary image as the output. The difficult in performing binarization is to find an appropriate threshold value. This paper presents a new adaptive binarization method, which determines the threshold value according to the brightness of local ridges and valleys. We experimentally show that the presented method results in better performance than a traditional method.

• 한국가시화정보학회:학술대회논문집
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• 2006.12a
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• pp.86-91
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• 2006

In this parer, we present the bubble forming and motion in the micro channel by using the two-dimensional numerical computation and experiment. In the numerical computation, The Lattice Boltzmann method(LBM) and free-energy model is used to treat the interfacial force and deformation of binary fluid system, drawn in to a micro channel and a numerical simulation is carried out by using the parallel computation method. The urn in this investigation is to examine the applicability of LBM to numerical analysis and experimental method of binary fluid separation and motion in the micro channel.

• Journal of Broadcast Engineering
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• v.18 no.3
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• pp.372-379
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• 2013

In this paper, we proposed a content-based image retrieval algorithm using local binary patterns and HSV color histogram. Images are retrieved using image input in image retrieval system. Many researches are based on global feature distribution such as color, texture and shape. These techniques decrease the retrieval performance in images which contained background the large amount of image. To overcome this drawback, the proposed method extract background fast and emphasize the feature of object by shrinking the background. The proposed method uses HSV color histogram and Local Binary Patterns. We also extract the Local Binary Patterns in quantized Hue domain. Experimental results show that the proposed method 82% precision using Corel 1000 database.

• Journal of the Korean Data and Information Science Society
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• v.12 no.2
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• pp.83-93
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• 2001

We investigate a kernel approach to discriminant analysis for binary classification as a machine learning point of view. Our view of the kernel approach follows support vector method which is one of the most promising techniques in the area of machine learning. As usual discriminant analysis, the kernel method can discriminate an object most likely belongs to. Moreover, it has some advantage over discriminant analysis such as data compression and computing time.

• Proceedings of the IEEK Conference
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• 2001.06b
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• pp.365-368
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• 2001

This paper described a design and implementation of the division/square-root for a redundant floating point binary number using high-speed quotient selector. This division/square-root used the method of a redundant binary addition with 25MHz clock speed. The addition of two numbers can be performed in a constant time independent of the word length since carry propagation can be eliminated. We have developed a 16-bit VLSI circuit for division and square-root operations used extensively in each iterative step. It peformed the division and square-root by a redundant binary addition to the shifted binary number every 16 cycles. Also the circuit uses the nonrestoring method to obtain a quotient. The quotient selection logic used a leading three digits of partial remainders in order to be implemented in a simple circuit. As a result, the performance of the proposed scheme is further enhanced in the speed of operation process by applying new quotient selection addition logic which can be parallelly process the quotient decision field. It showed the speed-up of 13% faster than previously presented schemes used the same algorithms.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.4
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• pp.2078-2093
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• 2019

Visual smoke recognition is a challenging task due to large variations in shape, texture and color of smoke. To improve performance, we propose a novel smoke recognition method by combining dual-encoded features that are extracted from both spatial and Curvelet domains. A Curvelet transform is used to filter an image to generate fifty sub-images of Curvelet coefficients. Then we extract Local Binary Pattern (LBP) maps from these coefficient maps and aggregate histograms of these LBP maps to produce a histogram map. Afterwards, we encode the histogram map again to generate Dual-encoded Local Binary Patterns (Dual-LBP). Histograms of Dual-LBPs from Curvelet domain and Completed Local Binary Patterns (CLBP) from spatial domain are concatenated to form the feature for smoke recognition. Finally, we adopt Gaussian Kernel Optimization (GKO) algorithm to search the optimal kernel parameters of Support Vector Machine (SVM) for further improvement of classification accuracy. Experimental results demonstrate that our method can extract effective and reasonable features of smoke images, and achieve good classification accuracy.

• Journal of Internet Computing and Services
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• v.12 no.5
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• pp.63-72
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• 2011

Binary translation is a kind of the emulation method which converts a binary code compiled on the particular instruction set architecture to the new binary code that can be run on another one. It has been mostly used for migrating legacy systems to new architecture. In recent, binary translation is used for instrumenting programs without modifying source code, because it enables inserting additional codes dynamically, For general application, there already exists some instrumentation software using binary translation, such as dynamic binary analyzers and virtual machine monitors. On the other hand, in order to be benefited from binary translation in kernel-level, a few issues, which include system performance, memory management, privileged instructions, and synchronization, should be treated. These matters are derived from the structure of the kernel, and the difference between the kernel and user-level application. In this paper, we present a scheme to apply binary translation and dynamic instrumentation on kernel. We implement it on Linux kernel and demonstrate that kernel-level binary translation adds an insignificant overhead to performance of the system.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.53 no.3
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• pp.152-163
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• 2004

This paper presents a sensorless speed control of cylindrical permanent magnet synchronous motors(PMSM) using an adaptive integral binary observer In view of composition with a main loop regulator and an auxiliary loop regulator, the binary observer has a property of the chattering alleviation in the constant boundary layer. However, the steady state estimation accuracy and robustness are dependent upon the width of the constant boundary. In order to improve the steady state performance of the binary observer, the binary observer is formed by adding extra integral dynamics to the switching hyperplane equation. With the help of integral characteristic, the rotor speed can be finely estimated and utilized for a sensorless speed controller for PMSM. Since the Parameters of the dynamic equations such as machine inertia or a viscosity friction coefficient are lot well known, there are many restrictions in the actual implementation. The proposed adaptive integral binary observer applies an adaptive scheme so that observer may overcome the problem caused by using the dynamic equations and the rotor speed is constructed by using the Lyapunov function. The observer structure and its design method are described. The experimental results of the proposed algorithm are presented to demonstrate the effectiveness of the approach.