• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.19 no.2
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• pp.146-154
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• 2023

In nuclear power plants, ultrasonic test for pipe wall thickness measurement is used during periodic inspections to prevent pipe rupture due to pipe wall thinning. However, when measuring pipe wall thickness using ultrasonic test, a significant amount of measurement error occurs due to the on-site conditions of the nuclear power plant. If the maximum pipe wall thinning rate is decided by the measured pipe wall thickness containing a significant error, the pipe wall thinning rate data have significant uncertainty and systematic overestimation. This study proposes preprocessing of pipe wall thinning measurement data using support vector machine regression algorithm. By using support vector machine, pipe wall thinning measurement data can be smoothened and accordingly uncertainty and systematic overestimation of the estimated pipe wall thinning rate data can be reduced.

• Journal of the Korean Association of Geographic Information Studies
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• v.2 no.2
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• pp.1-8
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• 1999

Information representing the thickness of the original lines from the thinning results can be used efficiently in order to implement the automated vectorizing system. This paper proposes a preprocessing scheme of thinning which can show the information of the original lines' thickness from the thinning result. In the proposed scheme, the depth of each pixel constructing the lines was calculated, which was represented by the number of layers composed of neighboring pixels surrounding the original pixel. And then the original lines' thickness could be recognized through the depth information of the skeleton from the thinning results. We implemented the proposed scheme and experimented on a contour map. Using the depth information of the skeleton, we could easily distinguish each line of the contour either an intermediate or an index contour.

• Journal of the Institute of Convergence Signal Processing
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• v.14 no.2
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• pp.90-94
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• 2013

Research for Manchu character digitalization is at an early stage. This paper proposes a preprocessing algorithm for Manchu character recognition. This algorithm improves the existing Hilditch thinning algorithm so that it corrects thinning error for Manchu characters. The existing algorithm separates the characters into the left-hand side and right-hand side, while our alogorithm uses the central point between the points that strokes exist when it classifies each of characters. The experimentation results show that this method is valid for thinning and classification of Manchu characters.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.29B no.8
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• pp.35-43
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• 1992

We have presented the tracing algorithm for center pixel of character image. Character image was read by scanner device. Performing the tracing process, it can be possible to detect feature points, such as branch point, stroke of 4 directions. So, the tracing process covers the thinning and feature point detection process for improving the processing time. Usage of suggested tracing algorithm instead of thinning that is the preprocessing of character recognition increases speed up to 5 times. The preprocessing chip has been designed by using single layer perceptron algorithm.

• Proceedings of the IEEK Conference
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• 2004.08c
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• pp.814-818
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• 2004

Off-line handwritten character recognition is in difficulty of incomplete preprocessing because it has not dynamic and timing information besides has various handwriting, extreme overlap of the consonant and vowel and many error image of stroke. Consequently off-line handwritten character recognition needs to study about preprocessing of various methods such as binarization and thinning. This paper considers running time of watershed algorithm and the quality of resulting image as preprocessing For off-line handwritten Korean character recognition. So it proposes application of effective watershed algorithm for segmentation of character region and background region in gray level character image and segmentation function for binarization image and segmentation function for binarization by extracted watershed image. Besides it proposes thinning methods which effectively extracts skeleton through conditional test mask considering running time and quality. of skeleton, estimates efficiency of existing methods and this paper's methods as running time and quality. Watershed image conversion uses prewitt operator for gradient image conversion, extracts local minima considering 8-neighborhood pixel. And methods by using difference of mean value is used in region merging step, Converted watershed image by means of this methods separates effectively character region and background region applying to segmentation function. Average execution time on the previous method was 2.16 second and on this paper method was 1.72 second. We prove that this paper's method removed noise effectively with overlap stroke as compared with the previous method.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.5
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• pp.775-783
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• 1990

In this paper we implemented the fast thinning unit by modifying the pipeline architecture which was proposed by Stanley R. Sternberg. The unit is useful in preprocessing such as image representation and pattern recognition etc. This unit is composed of interface part, local memory part, address generation part, thinning processing part and control part. In thinning processing part, we shortened the thinning part which performed by means of look up table using window mapping table. Thus we improved the weakness of SAP, in which the number of delay pipeline and window pipeline are equal to image column size. Two independent memorys using tri-state buffer enable the two direction flow of address generated by address generation part. This unit avoids the complexity of architecture and has flexibility of image size by means of simple modification of logic bits.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.365-365
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• 2000

In this paper, we describe the system to recognize the six digit postal number of mails using neural network. Our zip-code recognition system consists of a preprocessing procedure for the original captured image, a segmentation procedure for separating an address block area with a shape, and recognition procedure for the cognition of a postal number. we extract the feature vectors that are the input of a neural network for the recognition process based on an area optimizing and an image thinning processing. The neural network classifies the zip-code in the mail and the recognized zip-code is verified through the zip-code database.

• The KIPS Transactions:PartB
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• v.8B no.6
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• pp.651-656
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• 2001

In this paper, we propose Improved Self-Organized Graph(Improved SOG：$SOG^*$)thinning method, which maintains the excellent thinning results of Self-organized graph(SOG) built from Self-Organizing features map and improves the performance of modified SOG using a new incremental learning method of Kohonen features map. In the experiments, this method shows the thinning results equal to those of SOG and the time complexity O((logM)3) superior to it. Therefore, the proposed method is useful for the feature extraction from digits and characters in the preprocessing step.

• Journal of the Korean Institute of Telematics and Electronics
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• v.27 no.6
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• pp.929-936
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• 1990

This paper describes the method of the Korean character recognition by means of feature points extraction. Also, the preprocessing neural chip for noise elimination, smoothing, thinning and feature point extraction has been designs. The subpatterns were separated by means of advanced index algorithm using mask, and recognized by means of feature points classification. The separation of the Korean character subpatterns was abtained about 97%, and the recognition of the Korean characters was abtained about 95%. The preprocessing neural chip was simulated on SPICE and layouted by double CMOS 2\ulcorner design rule.

• Journal of the Korean Institute of Telematics and Electronics
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• v.14 no.5
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• pp.15-21
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• 1977

The syntactic pattern recognition system of Korean characters is composed of three main functional parts; Preprocessing, Graph-representation, and Segmentation. In preprocessing routine, the input pattern has been thinned using the Hilditch's thinning algorithm. The graph-representation is the detection of a number of nodes over the input pattern and codification of branches between nodes by 8 directional components. Next, segmentation routine which has been implemented by top down nondeterministic parsing under the control of tree grammar identifies parts of the graph-represented Pattern as basic components of Korean characters. The authors have made sure that this system is effective for recognizing Korean characters through the recognition simulations by digital computer.