• The Transactions of the Korea Information Processing Society
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• v.7 no.10
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• pp.3155-3163
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• 2000

In the recognitionsystem of car license plate, it is very important to extract the character from the license plate and recognize the extrated character. In this paper, I use the adaptive algorithm to recognize the charactor of licensse plate image. The adaptive algorithm is compounded of thinning algorithm template matching,algarthm, vector algorithm and so on. The adaptive algorithm was used to recognize the character from license image. In the result of expenment, character recognition is about up to 90% with the adaptive algorithm for the character region.

• Korean Journal of Computational Design and Engineering
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• v.11 no.3
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• pp.172-182
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• 2006

This paper presents a method to convert 3D CAD model to an appropriate analysis model using wrap-around, smooth-out and thinning operators that have been originally developed to realize the multi-resolution modeling. Wrap-around and smooth-out operators are used to simplify 3D model, and thinning operator is to reduce the dimension of a target object with simultaneously decomposing the simplified 3D model to 1D or 2D shapes. By using the simplification and dimension-reduction operations in an appropriate way, the user can generate an analysis model that matches specific applications. The advantage of this method is that the user can create optimized analysis models of various simplification levels by selecting appropriate number of detailed features and removing them.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.111-114
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• 2008

This paper proposes an effective hardware scheme for gabor filter and thinning stage processing of a fingerprint identification algorithm based on minutiae with 80% cycle occupation of 32-bit RISC microprocessor. The algorithm was developed based on minutiae with bifurcation and ending point. The analysis of an algorithm source rode was performed using ARM emulator.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1394-1397
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• 1987

It is difficult to detect edge segments from a noisy image since the image have a noise in piratical applications which utilize some type of visual input capability. Hence, the proposed algorithm consists of the modality tests based on parallel statistical tests without a noise removal preprocessing or postprocessing, and the edge detection technique With one-Pixel edge segments in this paper. The algorithm is very reliable and effective in the case of those situations where the Picture is poor quality and low resolution. And it does'nt require thinning operation and thresholding in hand. Experimental comparision With the more conventional techniques when applied to typical low-quality Pictures confirms good capabilities of the algorithm.

• Journal of Institute of Control, Robotics and Systems
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• v.3 no.2
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• pp.179-186
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• 1997

In this paper we suggest a development of surface defect inspection algorithms for cold mill strip. The defects which exist in a surface of cold mill strip have a scattering or singular distribution. This paper consists of preprocessing, feature extraction and defect classification. By preprocessing, the binarized defect image is achieved. In this procedure, Top-hit transform, adaptive thresholding, thinning and noise rejection are used. Especially, Top-hit transform using local min/max operation diminishes the effect of bad lighting. In feature extraction, geometric, moment and co-occurrence matrix features are calculated. For the defect classification, multilayer neural network is used. The proposed algorithm showed 15% error rate.

• Proceedings of the KIEE Conference
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• 2008.10b
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• pp.284-285
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• 2008

논문에서는 비전센서로 전방도로영상을 획득하여 차선인식과 정을 거쳐 자율주행에 필요한 도로정보를 추출하고 사고를 방지할 수 있게 경보음을 발생하는 기법을 제시한다. 비전을 통해 입력되는 정보중 직선도로나 곡선도로의 외곽에 해당하는 백색 선만을 인식하는 알고리즘이 필요하다. 이러한 알고리즘을 수행하기 위해서는 많은 계산량이 필요로 하기 때문에 실시간의 자율주행 시스템에의 적용은 제약이 수반된다. 본 논문은 이와 같은 문제를 해결하기 위해 세선화 영역 및 차선이탈경보시스템(LDWS) 알고리즘을 제시한다.

• Proceedings of the KIEE Conference
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• 1989.07a
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• pp.473-476
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• 1989

This paper proposes the recognition of Korean character by using the given pre-segmented area. For higher processing speed, we introduce the techniques for pruning the unused segments. And, new thinning algorithm is used for finding skeleton of each segment.

• Proceedings of the KSRS Conference
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• v.2
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• pp.643-646
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• 2006

This paper addresses the approach to extract linear features from satellite imagery using an efficient segmentation method. The extraction of linear features from satellite images has been the main concern of many scientists. There is a need to develop a more capable and cost effective method for the Iranian map revision tasks. The conventional approaches for producing, maintaining, and updating GIS map are time consuming and costly process. Hence, this research is intended to investigate how to obtain linear features from SPOT satellite imagery. This was accomplished using a discontinuity-based segmentation technique that encompasses four stages: low level bottom-up, middle level bottom-up, edge thinning and accuracy assessment. The first step is geometric correction and noise removal using suitable operator. The second step includes choosing the appropriate edge detection method, finding its proper threshold and designing the built-up image. The next step is implementing edge thinning method using mathematical morphology technique. Lastly, the geometric accuracy assessment task for feature extraction as well as an assessment for the built-up result has been carried out. Overall, this approach has been applied successfully for linear feature extraction from SPOT image.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.1315-1318
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• 2004

Based on fuzzy 2-mean classification and template matching method, we propose a new algorithm to detect the edges of an image. In the algorithm, fuzzy 2-mean classification can classify all pixels in the mask into two clusters whatever the mask in the dark or light region; and template matching not only determines the edge's direction, but also thins the detected edge by a set of inference rules and, by the way, reduces the impulse noises.

• The KIPS Transactions:PartB
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• v.9B no.4
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• pp.481-490
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• 2002

Off-line handwritten character recognition is in difficulty of incomplete preprocessing because it has not dynamic information 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 by extracted watershed image. Besides it proposes thinning methods that effectively extracts skeleton through conditional test mask considering routing time and quality of skeleton, estimates efficiency of existing methods and this paper's methods as running time and quality. 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.