• IEIE Transactions on Smart Processing and Computing
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• v.1 no.1
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• pp.17-26
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• 2012

This paper presents an image processing-based validation method for unrecognizable numbers in severely distorted license plate images which have been degraded by various factors including low-resolution, low light-level, geometric distortion, and periodic noise. Existing vehicle license plate recognition (LPR) methods assume that most of the image degradation factors have been removed before performing the recognition of printed numbers and letters. If this is not the case, conventional LPR becomes impossible. The proposed method adopts a novel approach where a set of reference number images are intentionally degraded using the same factors estimated from the input image. After a series of image processing steps, including geometric transformation, super-resolution, and filtering, a comparison using cross-correlation between the intentionally degraded reference and the input images can provide a successful identification of the visually unrecognizable numbers. The proposed method makes it possible to validate numbers in a license plate image taken under low light-level conditions. In the experiment, using an extended set of test images that are unrecognizable to human vision, the proposed method provides a successful recognition rate of over 95%, whereas most existing LPR methods fail due to the severe distortion.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.12
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• pp.2189-2196
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• 2016

This paper proposes a new finite control set-model predictive control (FCS-MPC) method for induction motors. In the method, the reference state that satisfies the given torque and rotor flux requirements is derived. Cost indices for the FCS-MPC are defined using the state tracking error, and a linear matrix inequality is formulated to obtain a proper weighting matrix for the state tracking error. The on-line procedure of the proposed FCS-MPC comprises of two steps: select the output voltage vector of the two level inverter minimizing the cost index and compute the optimal modulation factor of the minimizing output voltage vector in order to reduce the state tracking error and torque ripple. The steady state tracking error is removed by using an integrator to adjust the reference state. The simulation and experimental results demonstrated that the proposed FCS-MPC shows good torque, rotor flux control performances at different rotating speeds.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.846-853
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• 2018

In this paper, an improved model predictive control (MPC) method is proposed, which reduces the amount of calculations caused by the increased number of candidate voltage vectors with the increased voltage level in multi-level inverters. When the conventional MPC method is used for multi-level inverters, all candidate voltage vectors are considered to predict the next-step current value. However, in the case that the sampling time is short, increased voltage level makes it difficult to consider the all candidate voltage vectors. In this paper, the improved MPC method which can get a fast transient response is proposed with a small amount of the computation by adding new candidate voltage vectors that are set to find the optimal vector. As a result, the proposed method shows faster transient response than the method that considers the adjacent vectors and reduces the computational burden compared to the method that considers the whole voltage vector. the performance of the proposed method is verified through simulations and experiments.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.52 no.12
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• pp.675-683
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• 2003

This paper describes the correction strategy of an overcurrent relay applied in the linked line for interconnecting wind farm with utility power networks in order to improve the capability of a fault detection. The fault current measured in a relaying point might vary according to the fault conditions. Generally, the current of the line to line fault or the line to ground fault in the linked line is much higher than the set value of protective relay due to the large fault level. However, when the high impedance fault occurs in the linked line, we can't detect it by conventional set value because its fault level may be lower than the generating capacity of wind farm. And, the protective relay with conventional set value may generate a trip signal for the insertion of wind turbine generators due to the large transient characteristics. In order to solve above problems and improve protective relaying algorithms applied in the linked line, we propose a new correction strategy of the protective relay in the linked line. The presented method can detect the high impedance fault which can't be detected by conventional relay set value and may prevent the mis-operation of protective relay caused by the insertion of wind farm.

• Proceedings of the KSRS Conference
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• v.2
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• pp.610-614
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• 2006

In this paper the advanced method of geodesic active contours was developed for the task of building detection from aerial and satellite images. Automatic extraction of man-made structures including buildings, building blocks or roads from remote sensing data is useful for land use mapping, scene understanding, robotic navigation, image retrieval, surveillance, emergency management procedures, cadastral etc. A level set method based on a region-driven segmentation model was implemented with which building boundaries were detected, through this curve propagation technique. The essence of this approach is to optimize the position and the geometric form of the curve by measuring information along that curve, and within the regions that compose the image partition. To this end, one can consider uniform intensities inside objects and the background. Thus, given an initial position of the curve, one can determine global, region-driven functions and provide a statistical description of the inside and outside object area. The calculus of variations and a gradient descent method was used to optimize the variational functional by an iterative steady state process. Experimental results demonstrate the potential of the proposed processing scheme.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1996.11a
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• pp.524-528
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• 1996

Quality information is known to have the characteristic of continuous distribution in many manufacturing processes. It is difficult to describe the process condition by classifying the distribution into discrete ranges which is based on the set concept. Fuzzy control chart has been developed for the control of linguistic data but it still utilizes the dichotomous notion of classical set theory. In this paper, the fuzzy sampling method is studied in order to manage the ambiguous data properly and incorporated for generating fuzzy control chart. The method is based on the fuzzy set concept and considered to be appropriate for the realization of a complete fuzzy control chart. The fuzzy control chart was compared with the conventional generalized p-chart in the sensitivity for quality distribution and robustiness against the noise. The fuzzy control chart with the fuzzy sampling method showed better characteristics.

• Proceedings of the IEEK Conference
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• 2000.06b
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• pp.137-140
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• 2000

In this paper, we have proposed an efficient test generation method for asynchronous circuits. The test generation is based on specification level, especially on Signal Transition Graph(STG)〔1〕 which is a kind of specification method for asynchronous circuits. To conduct a high-level test generation, we have defined a high-level fault model, called single State Transition Fault(STF) model on STG and proposed a test generation algorithm for STF model. The effectiveness of the proposed fault model and its test generation algorithm is shown by experimental results on a set of benchmarks given in the form of STG. Experimental results show that the generated test for the proposed fault model achieves high fault coverage over single input stuck-at fault model with low cost. We have also proposed extended STF model with additional gate-level information to achieve higher fault coverage in cost of longer execution time.

• Journal of the Society of Naval Architects of Korea
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• v.39 no.3
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• pp.18-27
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• 2002

In order to improve the accuracy of the solution near the boundary in an analysis of viscous flow around an arbitrary boundary which move and be deformed using an Eulerian concept, a level-set based grid deformation method is introduced to concentrate grid points near the boundary. This paper presents a new monitor function which can easily control the level of the concentration of grid points along the boundary. Computations for steady flow around a semi-circular cylinder mounted on the bottom of the flow domain were carried out to check the improvement of the solution using the adaptive grid system with an immersed boundary method. The present numerical results show a good agreement with the solutions obtained by a body fitted grid system and more accurate solutions than those computed with non-adaptive grid system. For the validation of mechanical usefulness of the present method, an expanded analysis of flow around multi-body fixed in the flow domain was carried out. Finally, the present moving adaptive grid method was applied to a two-dimensional bubble rise problem. The computed results show well adapted grid points around the boundary of the bubble at every time and a good agreement with the result calculated by fixed grid system.

• International journal of advanced smart convergence
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• v.12 no.4
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• pp.134-141
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• 2023

We present a novel method aimed at refining ground truth data through regularization and modification, particularly applicable when working with the original ground truth set. Enhancing the performance of deep neural networks is achieved by applying regularization techniques to the existing ground truth data. In many machine learning tasks requiring pixel-level segmentation sets, accurately delineating objects is vital. However, it proves challenging for thin and elongated objects such as blood vessels in X-ray coronary angiography, often resulting in inconsistent generation of ground truth data. This method involves an analysis of the quality of training set pairs - comprising images and ground truth data - to automatically regulate and modify the boundaries of ground truth segmentation. Employing the active contour model and a recursive ground truth generation approach results in stable and precisely defined boundary contours. Following the regularization and adjustment of the ground truth set, there is a substantial improvement in the performance of deep neural networks.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.5
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• pp.571-575
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• 2010

Mutation testing is known as a very useful technique for measuring the effectiveness of a test data set and finding weak points of the test set. An equivalent mutant degrades the effectiveness of mutation testing. Elimination of equivalent mutants is a very important problem in mutation testing.In this paper, we proposed kinds of methods for detecting class-level equivalent mutants. These methods judge the equivalency of mutants through structural informations and behavioral information of the original program and mutants using static analysis. We found that our approach can detect not a few of equivalent mutants and expected that the cost of mutation testing can be saved considerably.