• Journal of the Korea Society of Computer and Information
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• v.14 no.8
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• pp.43-50
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• 2009

Text information in a digital video provides crucial information to acquire semantic information of the video. In the proposed method. text candidate regions are extracted from input sequence by using characteristics of stroke and text candidate regions are localized by using projection to produce text bounding boxes. Bounding boxes containing text regions are verified geometrically and each bounding box existing same location is tracked by calculating matching measure. which is defined as the mean of absolute difference between bounding boxes in the current frame and previous frames. Finally. text regions are enhanced using temporal redundancy of bounding boxes to produce final results. Experimental results for various videos show the validity of the proposed method.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.45 no.4
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• pp.59-70
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• 2008

In this paper, we proposed image processing technique for automatic real-time fire and smoke detection in tunnel environment. To avoid the large scale of damage of fire occurred in variety environments, it is purposeful to propose many studies to minimize and to discover the incident as fast as possible. But we need new specific algorithm because tunnel environment is quite different and it is difficult to apply previous fire detection algorithm to tunnel environment. Therefore, in this paper, we proposed specific algorithm which can be applied in tunnel environment. To minimize false detection in tunnel we used color and motion information. And it is possible to detect exact position in early stage with detection, test, verification procedures. In addition, by comparing properties of each algorithm throughout experiment, we have proved the validity and efficiency of proposed algorithm.

• Journal of the Korea Society of Computer and Information
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• v.12 no.2 s.46
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• pp.77-82
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• 2007

In this paper, we proposed the image processing techniques for extracting the cracks in a concrete surface crack image and the enhanced Max-Min neural network for recognizing the directions of the extracted cracks. The image processing techniques used are the closing operation or morphological techniques, the Sobel masking for extracting for edges of the cracks, and the iterated binarization for acquiring the binarized image from the crack image. The cracks are extracted from the concrete surface image after applying two times of noise reduction to the binarized image. We proposed the method for automatically recognizing the directions of the cracks with the enhanced Max-Min neural network. Also, we propose an enhanced Max-Min neural network by auto-tuning of learning rate using delta-bar-delta algorithm. The experiments using real concrete crack images showed that the cracks in the concrete crack images were effectively extracted and the enhanced Max-Min neural network was effective in the recognition of direction of the extracted cracks.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.6
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• pp.741-747
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• 2012

In this paper, we propose a fast and robust framework for detecting and tracking multiple targets. The proposed system includes two modules: object detection module and object tracking module. In the detection module, we preprocess the input images frame by frame, such as gray and binarization. Next after extracting the foreground object from the input images, morphology technology is used to reduce noises in foreground images. We also use a block-based histogram analysis method to distinguish human and other objects. In the tracking module, color-based tracking algorithm and Kalman filter are used. After converting the RGB images into HSV images, the color-based tracking algorithm to track the multiple targets is used. Also, Kalman filter is proposed to track the object and to judge the occlusion of different objects. Finally, we show the effectiveness and the applicability of the proposed method through experiments.

• Journal of the Korea institute for structural maintenance and inspection
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• v.16 no.1
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• pp.64-77
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• 2012

In this study, the crack detecting system with digital image processing techniques based on the mathematical morphology method was developed to detect cracks in concrete structures. In the developed system, the image combining technique of reconstructing multiple images as an entire single image considering efficient management of analysis results was applied as an additional module. The developed system was verified through a field test with the cracked concrete culvert and the crack width of 0.2 mm was able to be detected in the 40m span. In the image analysis, the difference between calculated crack width and actual crack width were less than 0.08mm. For image combination in the stitching test of pattern images, the stitched image was identical with the original picture of entire subject in the visual perception level.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.4
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• pp.494-499
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• 2012

In this paper, a new method for detecting various objects that can be risks to safety navigation in sea environment is proposed. By analysing Infrared(IR) images obtained from various sea environments, we could find out that object regions include both horizontal and vertical direction edges while background regions of sea surface mainly include vertical direction edges. Therefore, we present an approach to detecting object regions considering horizontal and vertical edges. To this end, in the first step, image enhancement is performed by suppressing noises such as sea glint and complex clutters using a statistical filter. In the second step, a horizontal edge map and a vertical edge map are generated by 1-D Discrete Cosine Transform technique. Then, a combined map integrating the horizontal and the vertical edge maps is generated. In the third step, candidate object regions are detected by a adaptive thresholding method. Finally, exact object regions are extracted by eliminating background and clutter regions based on morphological operation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.379-385
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• 2008

콘크리트 건물의 보수 작업은 표면에 발생하는 균열을 정확하게 계측함으로써 비용적인 측면과 안전성이 결정된다. 하지만 표면에 발생한 균열은 대부분 점검자에 의해 수작업으로 계측되기 때문에 시간적 측면에서 비효율적이다. 따라서 본 논문에서는 콘크리트 슬래브 표면에 발생한 균열의 밝기와 밀도 그리고 면적 특징을 이용한 균열 검출 기법을 제안한다. 제안된 균열 검출 방법은 콘크리트 슬래브 표면의 명암도와 위치 정보를 ART2 기반 양자화에 적용한 후, 균열과 인접한 배경간의 명암도 차이를 이용하여 균열과 인접한 배경을 분리한다. 균열과 인접한 배경이 분리된 영상에서 형태학적인 정보를 이용하여 세부적인 잡음을 제거한 후에 최종적으로 균열 영역을 검출한다. 실제 콘크리트 균열 영상을 대상으로 실험한 결과, 다양한 콘크리트 균열 영상에서 기존의 방법보다 균열 검출 성능이 개선되었음을 확인하였다.

• 한국HCI학회:학술대회논문집
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• 2007.02a
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• pp.553-560
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• 2007

본 논문에서는 양손의 터치를 인식하여 실시간 상호작용이 가능한 테이블 탑 디스플레이 시스템 및 구현 알고리즘에 대해 기술한다. 제안하는 시스템은 FTIR(Frustrated Total Internal Reflection) 메커니즘을 기반으로 제작되었으며 multi-touch, multi-user 방식의 손 제스처 입력이 가능하다. 시스템은 크게 영상 투영을 위한 빔-프로젝터, 적외선 LED를 부착한 아크릴 스크린, Diffuser 그리고 영상을 획득하기 위한 적외선 카메라로 구성되어 있다. 시스템 제어에 필요한 제스처 명령어 종류는 상호작용 테이블에서의 입력과 출력의 자유도를 분석하고 편리함, 의사소통, 항상성, 완벽함의 정도를 고려하여 규정하였다. 규정된 제스처는 사용자가 상호작용을 위해 스크린에 접촉한 손가락의 개수, 위치, 그리고 움직임 변화를 기준으로 세분화된다. 적외선 카메라를 통해 입력받은 영상은 잡음제거 및 손가락 영역 탐색을 위해 간단한 모폴로지 기법이 적용된 후 인식과정에 들어간다. 인식 과정에서는 입력 받은 제스처 명령어들을 미리 정의해놓은 손 제스처 모델과 비교하여 인식을 행한다. 세부적으로는 먼저 스크린에 접촉된 손가락의 개수를 파악하고 그 영역을 결정하며 그 후 그 영역들의 중심점을 추출하여 그들의 각도 및 유클리디언 거리를 계산한다. 그리고 나서 멀티터치 포인트의 위치 변화값을 미리 정의해둔 모델의 정보와 비교를 한다. 본 논문에서 제안하는 시스템의 효율성은 Google-earth를 제어하는 것을 통해 입증될 수 있다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2010.05a
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• pp.569-571
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• 2010

In this paper, we develop a vision inspection system for inspecting flaws on plastic products such as insufficient moldings, spots, scratches. The inspection algorithm for this system consist of image binarization for curved structure of plastic products, image noise removal using morphology operation, labeling methods for candidate regions and image filtering and calibration method for flaw inspection. In order to improve its performance, we also develop fast image processing algorithm based on GUI. To verify the effectiveness of this system, we conducted evaluation for the system accuracy and the inspection algorithm processing time.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.9
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• pp.353-361
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• 2012

In this paper, we propose a improvement method of vision inspector for T type welding nut using an auto sorting system. We used edge and thread detection with histogram of image which is captured by machine vision camera. We also used a binary morphology operation for a detection of spot. A major problem in this vision inspector is abnormal operation caused by degradation of image acquired. These degradations caused by oil pollution on conveyer belt. For overcome this problem, we introduce a pre-processing using a masked histogram equalization on the image acquired. Histogram equalization is applied on masked region (nut part) for increase contrast. As a result, we can remove features caused by oil pollution on background and reduce a ratio of abnormal operation from 10.0 % to 0.2 %.