• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.5
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• pp.883-891
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• 1994

In this paper, we introduce new thinning algorithm which is useful for handwritten Korean character by using pixel directivity. At first, the directivity detection is performed before thinning. Each pixel is classified into the straight line of the oblique line based on its directivity. The algorithm using Rutovitz corossing number is applied to the straight line. And the algorithm using Hilditch crossing number is applied to the oblique line. The proposed algorithm is compared with six convention algorithms. Comparison criteria are similarity, noisy branch, and phoneme segmentation rate. Experiments with 570 characters have been conducted. Experimental result shows that the proposed algorithm is superior to six conventional algorithm with respect to similarity and phoneme segmentation rate.

• 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.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2004.05a
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• pp.18-18
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• 2004

지도작성은 이동로봇의 주행 및 위치추정을 위해 반드시 필요한 요소이다. 이러한 지도작성에는 격자지도와 토폴로지컬 지도의 두 종류가 있다. 격자지도는 전체 환경을 작은 격자로 나누어 각각에 점유되어 있는 확률간을 부여함으로써 지도상의 모든 메트릭(metric) 정보를 나타내는 반면에, 토폴로지컬 지도는 메트릭 정보를 가짐으로써 위치추정을 가능하게 하는 노드와 이를 연결하는 에지로 표현된다.(중략)

• Proceedings of the IEEK Conference
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• 1999.11a
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• pp.1101-1104
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• 1999

This paper performed a comparative study on contour tracing based thinning algorithms. These algorithms are widely used for extracting skeleton due to its superiority to other techniques in processing speed to perform comparison. We selected general eight images consisted of fingerprints, characters, and figures. According to experimental results, we compared each algorithm in performance and ability made skeleton.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.18 no.2
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• pp.157-168
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• 1993

In this paper, it is shown that neural networks trained with back propagation algorithm and dictionary can be applied to recognize handwritten English characters. To eliminate the useless data part and to minimize the variety of characters from the scanned image file, various preprocessings : that is, segmentation, centering, noise filtering, sealing and thinning are performed. After these, characteristic features are derived from thinned character pattern. The neural network is trained by using the extracted features for sample data, and all test data are classified into English alphabets according to their features through the neural network. Finally, the ways of reducing learning time and improving recognition rate, and the relationship between learning time and hidden layer nodes are considered. As a result of this study, after successful training, a high recognition rate has been obtained with this system for the trained patterns and about 93% for test patterns. Using dictionary, the recognition rate was about 97% for test pattern.

• Journal of Korea Water Resources Association
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• v.38 no.10 s.159
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• pp.841-849
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• 2005

Two-phase flows, e.g. sediment-laden flow and bubbly flow, have two different flow profiles; flow velocity and sediment velocity. To measure velocity distributions of two-phase flows, it is necessary to use sophisticated instruments which can separate velocity profiles of two-phases. For bubbly flows, PIV (Particle Image Velocimetry) or PTV (Particle Tracking Velocimetry) has given fairly good velocity profiles of two-phases. However, for sediment-laden flows, the applications of PIV or PTV has not been so successful, because the sediment particles introduced to the flow kept the images from being analyzed. A new algorithm, which consists of several image analysis methods, is proposed to analyze sediment-laden flows. For detection algorithm, threshold method, edge detection method, and thinning method are adapted, and for finding matching pair PIV and PTV routines are combined. The proposed method can (1) detect sediment particles with irregular boundaries, (2) remove reflected images and scattered images, and (3) discriminate tracer particles from reflected images of sediment particles.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.45 no.5
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• pp.110-116
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• 2008

This paper presents a new postprocessing method to eliminate the false minutiae, that caused by the skelectonization of fingerprint image, and an image compression method using Isometric Self Organizing Map(ISOSOM). Since the SOM has simple structure, fast encoding time, and relatively good classification characteristics, many image processing areas adopt this such as image compression and pattern classification, etc. But, the SOM shows limited performances in pattern classification because of it's single layer structure. To maximize the performance of the pattern classification with small code book, we a lied the Isometric SOM with the isometry of the fractal theory. The proposed Isometric SOM postprocessing and compression algorithm of fingerprint image showed good performances in the elimination of false minutiae and the image compression simultaneously.