• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 1999년도 Proceedings of International Symposium on Remote Sensing
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• pp.177-181
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• 1999

This paper presents an algorithm for building detection from aerial image using segment measure function and line relation. In the detection algorithm proposed, edge detection, linear approximation and line linking are used and then line measure function is applied to each line segment in order to improve the accuracy of linear approximation. Parallelisms, orthogonalities are applied to the extracted liner segments to extract building. The algorithm was applied to aerial image and the buildings were accurately detected.

• 전기전자학회논문지
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• 제20권1호
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• pp.82-88
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• 2016

영상 인식에서 널리 이용되는 PPHT(Progressive Probability Hough Transform)는 직선을 정확하게 인식하는 우수한 알고리즘이나 원본 영상이 선명하지 않거나 복잡하여 잡음 성분이 많은 경우 인식률이 감소하는 문제가 있다. 이러한 문제를 해결하기 위해 잡음에 강하고 손상된 가장자리 패턴을 복구하며 직선을 인식하는 개선된 PPHT 방식을 제안한다. 제안하는 알고리즘은 픽셀 단위로 직선을 추적하고 검증하여 선분을 검출하는 방식으로 잡음의 영향을 최소화하고 손상된 가장자리 패턴을 일정 범위 내에서 복구하여 인식률을 증가시켰다. 제안한 알고리즘을 차선 인식에 적용하여 직선의 오인식률을 30% 이상 감소시키고 선분 인식률이 15%까지 증가함을 확인하였다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1990년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 26-27 Oct. 1990
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• pp.1228-1233
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• 1990

This paper proposes a robust on-line fault detection method for uncertain systems. It is based on the fault detection method [10] accounting for modelling errors, which is shown to have superior performance over traditional methods but has some computational problems so that it is hard to be applied to on-line problems. The proposed method in this paper is an on-line version of the fault detection method suggested in [10]. Thus the method has the same detection performance robust to model uncertainties as that of [10]. Moreover, its computational burden is shown to be considerably lessened so that it is applicable to on-line fault detection problems.

• 한국멀티미디어학회논문지
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• 제19권10호
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• pp.1747-1758
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• 2016

In this paper, we propose a new fast Hough transform to improve the processing time and line detection of Hough transform that is widely used in various vision systems. First, for the fast processing time, we reduce the number of features by using multi-statistical methods and also reduce the dimension of angle through six separate directions. Next, for improving the line detection, we effectively detect the lines of various directions by designing the line detection method which detects line in proportion to the number of features in six separate directions. The proposed method was evaluated with previous methods and obtained the excellent results. The processing time was improved in about 20% to 50% and line detection was performed better in various directions than conventional methods with experimental images.

• 융합신호처리학회논문지
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• 제14권2호
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• pp.82-89
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• 2013

본 논문에서는 화상에 존재하는 디지털 직선을 고정밀도로 검출하는 방법을 제안한다. 화상의 크기를 $N{\times}N$로 하면, 이 계산량은 $O(N^4)$이지만 실제 사용하기는 곤란하므로, 검출 정밀도의 열화를 억제하면서 계산량을 $O(N^3)$로 하는 알고리즘을 검토하였다. 국소영역에서 Hough 변환하여 추출된 선분을 연신처리(stretching treatment)하고, 화상으로부터 직선을 검출하는 방법은 길거나 짧은 여러 가지의 직선을 고속으로 검출할 수 있는 훌륭한 방법이지만, 기울어진 선분의 검출 정밀도는 약간 떨어진다. 본 논문에서는 사선의 검출 정밀도를 향상시킨 직선 검출방법을 국소영역에 적용함으로써 처리속도가 감소되지 않고, 직선을 고정밀도로 검출하는 방법에 관해서 논술한다. 실험 결과 제안된 방법은 기존의 방법과 같은 정도 이하의 시간에서 정밀도가 높은 직선을 검출할 수 있다는 것을 확인하였다.

• 한국컴퓨터정보학회논문지
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• 제20권12호
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• pp.29-36
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• 2015

In this paper, we propose the horizontal line detection using the Haar-like features and linear regression in infrared images. In the marine environment horizon image is very useful information on a variety of systems. In the proposed method Haar-like features it was noted that the standard deviation be calculated in real time on a static area. Based on the pixel position, calculating the standard deviation of the around area in real time and, if the reaction is to filter out the largest pixel can get the energy map of the area containing the straight horizontal line. In order to select a horizontal line of pixels from the energy map, we applied the linear regression, calculating a linear fit to the transverse horizontal line across the image to select the candidate optimal horizontal. The proposed method was carried out in a horizontal line detecting real infrared image experiment for day and night, it was confirmed the excellent detection results than the legacy methods.

• 한국정밀공학회지
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• 제17권10호
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• pp.119-124
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• 2000

One of the main problems in 3D shape measuring systems that use the triangulation of line-shaped laser light is precise center line detection of line-shaped laser stripe. The intensity of a line-shaped laser light stripe on the CCD image varies following to the reflection angles, colors and shapes of objects. In this paper, a new center line detection algorithm to compensate the local intensity variation on a line-shaped laser light stripe is proposed. The 3-D surface shape measuring system using the proposed center line detection algorithm can measure 3-D surface shape with enhanced measurement resolution by using the dynamic shape reconstruction with adaptive pattern clustering of the line-shaped laser light. This proposed 3-D shape measuring system can be easily applied to practical situations of measuring 3-D surface by virtue of high speed measurement and compact hardware compositions.

• Journal of Information Processing Systems
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• 제1권1호
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• pp.9-13
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• 2005

Computer security has become a critical issue with the rapid development of business and other transaction systems over the Internet. The application of artificial intelligence, machine learning and data mining techniques to intrusion detection systems has been increasing recently. But most research is focused on improving the classification performance of a classifier. Selecting important features from input data leads to simplification of the problem, and faster and more accurate detection rates. Thus selecting important features is an important issue in intrusion detection. Another issue in intrusion detection is that most of the intrusion detection systems are performed by off-line and it is not a suitable method for a real-time intrusion detection system. In this paper, we develop the real-time intrusion detection system, which combines an on-line feature extraction method with the Least Squares Support Vector Machine classifier. Applying the proposed system to KDD CUP 99 data, experimental results show that it has a remarkable feature extraction and classification performance compared to existing off-line intrusion detection systems.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제7권9호
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• pp.2312-2325
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• 2013

In this paper, we propose a preprocessing method that it is to correct the distortion of text area in Korean signboard images as a preprocessing step to improve character recognition. Distorted perspective in recognizing of Korean signboard text may cause of the low recognition rate. The proposed method consists of four main steps and eight sub-steps: main step consists of potential vertical components detection, vertical components detection, text-boundary estimation and distortion correction. First, potential vertical line components detection consists of four steps, including edge detection for each connected component, pixel distance normalization in the edge, dominant-point detection in the edge and removal of horizontal components. Second, vertical line components detection is composed of removal of diagonal components and extraction of vertical line components. Third, the outline estimation step is composed of the left and right boundary line detection. Finally, distortion of the text image is corrected by bilinear transformation based on the estimated outline. We compared the changes in recognition rates of OCR before and after applying the proposed algorithm. The recognition rate of the distortion corrected signboard images is 29.63% and 21.9% higher at the character and the text unit than those of the original images.

• 센서학회지
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• 제29권3호
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• pp.194-200
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• 2020

Human detection is an important aspect in many video-based sensing and monitoring systems. Studies have been actively conducted for the automatic detection of humans in camera images, and various methods have been proposed. However, there are still problems in terms of performance and computational cost. In this paper, we describe a method for efficient human detection in the field of view of a camera, which may be static or moving, through multiple processing steps. A detection line is designated at the position where a human appears first in a sensing area, and only the one-dimensional gray pixel values of the line are monitored. If any noticeable change occurs in the detection line, corner detection and optical flow computation are performed in the vicinity of the detection line to confirm the change. When significant changes are observed in the corner numbers and optical flow vectors, the final determination of human presence in the monitoring area is performed using the Histograms of Oriented Gradients method and a Support Vector Machine. The proposed method requires processing only specific small areas of two consecutive gray images. Furthermore, this method enables operation not only in a static condition with a fixed camera, but also in a dynamic condition such as an operation using a camera attached to a moving vehicle.