• Journal of information and communication convergence engineering
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• v.6 no.2
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• pp.204-206
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• 2008

In this paper, we proposed the recognition method that automatically extracts cracks from a surface image acquired by a digital camera and recognizes the directions (horizontal, vertical, -45 degree, and 45 degree) of cracks using the fuzzy single layer perceptron. We compensate an effect of light on a concrete surface image by applying the closing operation, which is one of the morphological techniques, extract the edges of cracks by Sobel masking, and binarize the image by applying the iterated binarization technique. Two times of noise reduction are applied to the binary image for effective noise elimination. After the specific regions of cracks are automatically extracted from the preprocessed image by applying Glassfire labeling algorithm to the extracted crack image, the cracks of the specific region are enlarged or reduced to $30{\times}30$ pixels and then used as input patterns to the fuzzy single layer perceptron. The experiments using concrete crack images showed that the cracks in the concrete crack images were effectively extracted and the fuzzy single layer perceptron was effective in the recognition of the extracted cracks directions.

• Journal of the Korea Society of Computer and Information
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• v.13 no.5
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• pp.19-26
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• 2008

In this paper, we converted an RGB into an YCbCr image input from CCD camera and then after compute difference two consecutive images, conduct Glassfire Labeling. We extract an image become ware of motion-change, if the difference between most broad(area) and Area critical value more than critical value. We enforce the detection of facial characteristics to an extracted motion-change images by using AdaBoost algorithm to extract an characteristics.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.9 no.7
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• pp.1575-1581
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• 2005

Recently, further study is being done on the affect of crack on concrete structure and many people have made every endeavor not to leave it unsettled but to minimize it by repair works. In this paper we propose the image processing method that do not remain manual but automatically process the length, the direction and e width of cracks on concrete surface. First, we calibrate light's affect from image by using closing operation, one of morphology methods that can extract the feature of oracle and we extract the edge of crack image by sobel mask. After it, crack image is binarized by iteration binarization. And we extract the edge of cracks using noise elimination method that use an average of adjacent pixels by 3${\times}$3 mask and Glassfire Labeling algorithm. on, in this paper we propose an image processing method which can automatically measure the length, the direction and the width of cracks using the extracted edges of cracks. The results of experiment showed that the proposed method works better on the extraction of concrete cracks. Also our method showed the possibility that inspector's decision is unnecessary.

• Journal of Advanced Navigation Technology
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• v.12 no.3
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• pp.280-285
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• 2008

The traditional face detection method is to use difference picture method are used to detect movement. However, most do not consider this mathematical approach using real-time or real-time implementation of the algorithm is complicated, not easy. This paper, the first to detect real-time facial image is converted YCbCr and RGB video input. Next, you convert the difference between video images of two adjacent to obtain and then to conduct Glassfire Labeling. Labeling value compared to the threshold behavior Area recognizes and converts video extracts. Actions to convert video to conduct face detection, and detection of facial characteristics required for the extraction and use of AdaBoost algorithm.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.05a
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• pp.361-363
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• 2013

비파괴 검사란 재료나 제품을 원형과 기능에 변화를 주지 않고 실시하여 원하는 정보를 획득할 수 있는 검사를 의미한다. 비파괴검사는 점검자의 육안 조사를 통한 수작업으로 이루어지고 있기 때문에 점검자의 주관이 개입되며, 점검자에 따라 검사 결과의 차이가 있을 수 있으므로 신뢰도의 차이가 발생하게 된다. 그러므로 본 논문에서는 비파괴 검사를 이용하여 획득한 세라믹 소재 영상에서 효율적으로 결함을 검출하는 방법을 제안한다. 제안된 방법은 세라믹 소재 영상에 가우시안 필터링 기법을 적용하여 잡음을 제거하고, Ends-in Search Stretching 기법을 적용하여 명암 대비를 강조한다. 명암 대비가 강조된 영상에 샤프닝 기법을 적용하여 윤곽선을 강조한다. 윤곽선이 강조된 영상에 $3{\times}3 $ Roberts 마스크를 적용하여 강조된 윤곽선을 추출하고, Glassfire 기법을 적용하여 라벨링한 후, 시그마 퍼지 이진화 기법과 형태학적 정보를 이용하여 잡음을 제거하고 결함 영역을 검출한다. 제안된 방법을 세라믹 소재 영상을 대상으로 실험한 결과, 효율적으로 결함을 검출하는 것을 확인할 수 있었다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.215-218
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• 2011

본 논문에서는 비파괴 검사를 이용하여 획득한 세라믹 소재 영상에서 효율적으로 결함을 검출하는 방법을 제안한다. 제안된 방법은 세라믹 소재 영상에 비등방성 필터링 기법과 가우시안 필터링 기법을 반복 적용하여 잡음을 제거하고, Ends-in Search Stretching 기법을 적용하여 명암 대비를 강조한다. 명암 대비가 강조된 영상에 $7{\times}7$ Sobel 마스크를 적용하여 윤곽선을 추출한 후, 임계치 이진화 기법을 적용하여 영역을 세분화하기 위한 기울기를 계산한다. 계산된 기울기를 이용하여 영상을 세분화한 후에 Glassfire 기법을 적용한다. Glassfire 기법이 적용된 영상과 Ends-in Search Stretching 기법이 적용된 영상을 비교하여 중복되는 영역만을 추출한다. 추출된 영역에 퍼지 이진화 기법과 침식 연산을 적용하여 잡음을 제거하고 결함을 검출한다. 제안된 방법을 세라믹 소재 영상을 대상으로 실험한 결과, 기존의 결함 검출 방법보다 효율적으로 결함이 검출되는 것을 확인할 수 있었다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.5
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• pp.843-848
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• 2008

Most of face detection technique uses information from the face of the movement. The traditional face detection method is to use difference picture method ate used to detect movement. However, most do not consider this mathematical approach using real-time or real-time implementation of the algorithm is complicated, not easy. This paper, the first to detect real-time facial image is converted YCbCr and RGB video input. Next, you convert the difference between video images of two adjacent to obtain and then to conduct Glassfire Labeling. Labeling value compared to the threshold behavior Area recognizes and converts video extracts. Actions to convert video to conduct face detection, and detection of facial characteristics required for the extraction and use of AdaBoost algorithm.

• Journal of Advanced Navigation Technology
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• v.14 no.2
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• pp.191-197
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• 2010

Many does an application and application but the image analysis of face detection considerably is difficult. In order for with effect of the illumination which is irregular in the present paper America the illumination to range evenly in the face which is detected, detects a face territory, Complemented the result which detects only the front face of existing. With LAB color illumination revisions compared in Adaboost face detection of existing and 32% was visible the face detection result which improves. Bought two images which are input and executed Glassfire label rings. Compared Area critical price and became the area of above critical value and revised from RGB smooth anger and LAB images with LCFD system algorithm. The operational conversion image which is extracted like this executed a face territory detection in the object. In order to extract the feature which is necessary to a face detection used AdaBoost algorithms. The face territory remote login with the face territory which tilts in the present paper, until Multi-view face territory detections was possible. Also relationship without high detection rate seems in direction of illumination, With only the public PC application is possible was given proof user authentication field etc.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.2
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• pp.360-365
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• 2005

본 논문에서는 콘크리트 표면 균열 영상에서 균열을 효율적으로 추출하기 위한 화상처리 기법과 ART1 기반 RBF 네트워크를 제안하여 균열의 방향성을 인식한다. 본 논문에서 사용된 화상처리 기법으로는 균열 영상의 빛을 보정하기 위한 모폴로지 기법인 채움(Closing)연산을 적용하고 Sobel 마스크를 적용하여 균열 영상의 에지를 추출한 후 반복 이진화를 적용하여 균열 영상을 이진화한다. 이진화 된 영상에 두 차례에 걸쳐 잡음제거를 수행하여 콘크리트 표면 균열 영상으로부터 균열을 추출한다. 본 논문에서는 추출된 균열을 ART1 기반 RBF 네트워크에 적용하여 균열의 방향성(횡방향, 종방향, $-45^{\circ}$방향, $45^{\circ}$방향)을 자동으로 인식할 수 있는 방법을 제안한다. 제안된 ART1 기반 RBF 네트워크는 입력층과 중간층으로의 학습은 ART1을 적용하고 중간층과 출력층 간의 학습은 Delta 학습 방법을 적용한다. 실제 콘크리트 균열 영상을 적용하여 실험한 결과, 콘크리트 표면 균열 영상에서 효율적으로 균열을 추출할 수 있었고 제안된 ART1 기반 RBF 네트워크가 추출된 균열의 방향성 인식에 효율적인 것을 확인하였다.