• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.10
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• pp.104-111
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• 1997

It is known as a difficult problem to recognize text-background mixed documents. In this paper a new string extraction algorithm, using mathematical morphology for the document consisting of text and overlapped periodic background pattern, is proposed. The algorithm consists of pattern periodicity feature extraction and background removal. The extracted pattern periodicity feature is used to determine the shape of structuring elements for morphological pre- and post-processing to remove background. The effectiveness of the proposed algorithm over the existing one is also verified through the experiments with various test documents.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.1763-1766
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• 2003

This paper proposes a non-contact color inspection system for plasma display panel (PDP). The red, green, and blue test pattern images are acquired by using the area color CCD camera at the various distance from the PDP. The RGB values are obtained from the region of interest (ROI) which are extracted by applying the image processing to the test pattern image. Finally, the CIE xy and u'v' chromaticity coordinates of the test pattern images according to the distance are acquired from the RGB color coordinates.

• Transactions of Materials Processing
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• v.11 no.7
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• pp.614-619
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• 2002

For an accurate measurement of the material behavior of small structures, a new optical experimental technique is proposed to measure the deformation. The test method uses the dual microscope that can measure the relative deformation of two adjacent regions. The magnified view is captured by CCD cameras and the relative deformation can be measured by the pattern matching and tracing method. Using this experimental technique, the deformation of solder joints in electronic packaging and the strain of the nickel thin film are measured.

• Journal of Electrical Engineering and information Science
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• v.3 no.3
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• pp.342-347
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• 1998

An OptiNeural system is developed for optical pattern classification. It is a novel hybrid system which consists of an optical processor and a multilayer neural network. It takes advantages of two dimensional processing capability of an optical processor and nonlinear mapping capability of a neural network. The optical processor with a binary phase only filter is used as a preprocessor for feature extraction and the neural network is used as a decision system through mapping. OptiNeural system is trained for optical pattern classification by use of a simulated annealing algorithm. Its classification performance for grey tone texture patterns is excellent, while a conventional optical system shows poor classification performance.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2009.10a
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• pp.53-56
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• 2009

Roll forming process is one of important metal processing technology because the process is simple and economical. These days, roll forming process is tried to be employed in manufacturing the circuit board, barrier ribs and solar cell plate for productivity. However, it is difficult to apply to the forming of micro scale or sub-micro scale pattern. In this study, the roll forming processing for the micro scale is designed and analyzed. In this study, the forming of micro pattern for solar cell plate by incremental roll forming process is analyzed. The solar cell plate may have thousands of patterns, and the analysis of forming considering all the patterns is impossible due to the computational costs. In this study, analyses are carried out for various numbers of patterns and the results are compared. It is shown that the analyses results with four row patterns and twelve row patterns are same. So, it is considered that the analysis can be carried out for only four rows of pattern for the design of incremental roll forming process. Also experiment is carried out process that is designed through simulation.

• Journal of the Korean Society for Nondestructive Testing
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• v.13 no.2
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• pp.11-19
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• 1993

It is very essential to get the accurate classification of defects in primary pressure vessel weld for the safety of nuclear power plant. The signal analysis using the digital signal processing and pattern recognition is performed to classify UT defects extracting feature vector from ultrasonic signals. The minimum distance classifier and the maximum likelihood classifier based on statistics were applied in this experiment to discriminate ultrasonics data obtained form both the training specimens (slit, hole) and the testing specimens(crack, slag). The classification rate was measured using pattern classifier. Results of this study show the promise in solving the many flaw classification problems that exist today.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.640-643
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• 2003

A Walsh function based associative memory is capable of storing m patterns in a single pattern storage space with Walsh encoding of each pattern. Furthermore, each stored pattern can be matched against the stored patterns extremely fast using algorithmic parallel processing. As such, this special type of memory is ideal for real-time processing of large scale information. However this incredible efficiency generates large amount of crosstalk between stored patterns that incurs mis-recognition. This crosstalk is a function of the set of different sequencies [number of zero crossings] of the Walsh function associated with each pattern to be stored. This sequency set is thus optimized in this paper to minimize mis-recognition, as well as to maximize memory saying. In this paper, this Walsh memory has been applied to the problem of face recognition, where PCA is applied to dimensionality reduction. The maximum Walsh spectral component and genetic algorithm (GA) are applied to determine the optimal Walsh function set to be associated with the data to be stored. The experimental results indicate that the proposed methods provide a novel and robust technology to achieve an error-free, real-time, and memory-saving recognition of large scale patterns.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.4
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• pp.537-543
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• 2003

Transient vibration generated by developing localized fault in gear can be used as indicators in gear fault detection. This vibration signal suffers from the background noise such as gear meshing frequency and its harmonics and broadband noise. Thus in order to extract the information about the only gear fault from the raw vibration signal measured on the gearbox this signal is processed to reduce the background noise with many kinds of signal-processing tools. However, these signal-processing tools are often very complex and time waste. Thus. in this paper. we propose a novel approach detecting the damage of gearbox and analyzing its pattern using the raw vibration signal. In order to do this, the residual signal. which consists of the sideband components of the gear meshing frequent) and its harmonics frequencies, is extracted from the raw signal by the power spectral density (PSD) to obtain the information about the fault and is used as the input data of the artificial neural network (ANN) for analysis of the pattern of gear fault. This novel approach has been very successfully applied to the damage analysis of a laboratory gearbox.

• Proceedings of the Korean Society of Laser Processing Conference
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• 2006.11a
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• pp.114-117
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• 2006

Diffraction grating is the optical device which has periodic pattern. Decorative logotypes is the one of application of diffraction grating. In this paper diffraction grating for decorative logotype is fabricated by dot pattern in stead of line pattern. A metallic mold for diffraction gratings is fabricated with a mode-locked 12 ps $Nd:YVO_4$ laser. Laser pulses with a wavelength of 355nm are irradiated on the surface of NOK 80, a mold material, to generate dot patterns. In order to minimize the dot diameter, laser power is set just above the ablation threshold of NOK 80. Results show that the spectrum from the fabricated mold is good enough for some industrial application.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2009.05a
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• pp.56-59
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• 2009

Roll forming process is one of important metal processing technology because the process is simple and economical. These days, roll forming process is tried to be employed in manufacturing the circuit board, barrier ribs and solar cell plate for productivity. However, it is difficult to apply to the forming of micro scale or sub-micro scale pattern. In this study, the roll forming processing for the micro scale is designed and analyzed. In this study, the forming of micro pattern for solar cell plate by incremental roll forming process is analyzed. The solar cell plate may have thousands of patterns, and the analysis of forming considering all the patterns is impossible due to the computational costs. In this study, analyses are carried out for various numbers of patterns and the results are compared. It is shown that the analyses results with four row patterns and twelve row patterns are same. So, it is considered that the analysis can be carried out for only four rows of pattern for the design of incremental roll forming process.