• 전기학회논문지
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• 제56권7호
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• pp.1321-1323
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• 2007

A new reference point location method based on an edge map is proposed, where an orientation map is defined and used to find the edge map. Experimental results show that the proposed method can effectively detect the core point in poor quality and arch-type fingerprint images and produces better results in terms of the detection rate and accuracy than the sine map-based method.

• 한국멀티미디어학회논문지
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• 제21권2호
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• pp.300-309
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• 2018

Detection of vanishing point is a challenging task in the situations where there are several structures with straight lines. Commonly used approaches for determining vanishing points involves finding the straight lines using edge detection and Hough transform methods. This approach often fails to perform effectively when there are a lot of straight lines found. The lines not meeting at a vanishing point are considered to be noises. In such situation, finding right candidate lines for detecting vanishing points is not a simple task. This paper proposes to use reference objects for vanishing point detection. By analyzing a reference object, it identifies the contour of the object, and derives a polygon from the contour information. Then the edges of the detected polygon are used to find the vanishing points. Our experimental results show that the proposed approach can detect vanishing points with comparable accuracy to the existing edge detection based method. Our approach can also be applied effectively even to complex situations, where too many lines generated by the existing methods make it difficult to select right lines for the vanishing points.

• 한국정보보호학회:학술대회논문집
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• 한국정보보호학회 2002년도 종합학술발표회논문집
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• pp.417-420
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• 2002

본 논문에서는, 지문인증 시스템에 있어서 방향성분의 통계적 방법을 이용한 reference point 검출 알고리즘과 이 reference point를 중심으로 하여 기존의 filterbank의 단점을 개선한 feature 추출 알고리즘을 소개한다. 제안한 reference point검출 알고리즘은 기존의 Poincare방법의 단점인 세밀한 전처리 과정과 arch type의 지문에 대해 장점을 가지며, 개선한 filterbank방법은 기존의 filterbank방법보다 reference point의 검출 위치에 덜 민감하며, 좀 더 높은 인증률을 보였다.

• 전기학회논문지
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• 제56권8호
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• pp.1511-1513
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• 2007

A new reference point location method using the cosine component is proposed, where an edge map is defined and used to find the reference point. Because all processes used in the proposed method are performed at the block level, less processing time is required. Experimental results show that the proposed method can effectively detect the reference point with higher speed and accuracy for all types of fingerprints.

• Journal of electromagnetic engineering and science
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• 제12권1호
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• pp.70-76
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• 2012

We compare the detection probabilities of the time-reversal(TR) detection system and the conventional radar system. The target is assumed to be hidden inside a random medium such as a forest. We propose a TR detection system based on the SAR(Synthetic Aperture Radar) algorithm. Unlike the conventional SAR images, the proposed TR-SAR system has an interesting property. Specifically, the target-related signal components due to the time-reversal refocusing characteristics, as well as some of clutter-related signal components are concentrated at the time-reversal reference point. The remaining clutter-related signal components are scattered around that reference point. In this paper, we model the random media as a collection of point scatterers to avoid unnecessary complexities. We calculate the detection probability of the TR radar system based on the proposed simple random media model.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 제14회 신호처리 합동 학술대회 논문집
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• pp.437-440
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• 2001

본 논문에서는 지문인식 시스템에 있어서 중간 단계인 Reference Point를 검출하는 방법을 제안하려고 한다. Reference Point는 지문 인식 방법들인 Minutiae 매칭 방법[1]과 Gabor filter를 사용한 Filterbank 방법[2]을 적용함에 있어서 feature를 추출할 때 사용되는 기준이 되는 Point이다. 그래서 동일인에 대해서는 항상 불변하고 정확한 위치를 찾아내는 정도가 지문 인식 시스템의 인식률에 크게 영향을 미치게 된다. 본 논문에서 제안하는 방법은 Gray Image에서 직접 Statistical한 방법을 사용하여 지문의 방향 분포를 구하고 이러한 방향 분포도로부터 얻어진 정보를 바탕으로 각 방향간의 거리를 측정하여 모든 방향 성분을 동일하게 유지하는 Reference Region을 찾게 된다. 이렇게 추출된 Reference Region내에서 SED(Statistical Equi-Distance)를 최대로 하는 좌표값을 Reference Point로 결정하게 된다.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 한국자동제어학술회의논문집(국내학술편); 포항공과대학교, 포항; 24-26 Oct. 1996
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• pp.1360-1363
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• 1996

EPD(End Point Detection) is used to decide etching degree of layer which must be removed at wafer etching process in plasma etching process which is one of the most important process in semiconductor manufacturing. In this thesis, the method which detects malfunction of etching process in real-time will be discussed. Several EPD signal traces are collected in normal plasma etching condition and used as reference EPD signal traces. Critical points can be detected by applying differentiation and zero-crossing techniques to reference EPD signal. Mean and standard deviation of critical parameters which is memorized from reference EPD signal are calculated and these determine the lower and higher limit of control chart. And by applying statical control chart to EPD signals which are collected in real etching process malfunctions of process are detected in real-time. By means of applying this method to the real etching process we prove our method can accurately detect the malfunction of etching process and can compensate disadvantage of current industrial method.

• 융합신호처리학회논문지
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• 제19권1호
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• pp.1-6
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• 2018

본 논문에서는 다중 스케일 영상 공간에서 특징점 검출을 위해 수행되는 반복적인 과정을 제거하는 방법을 제안한다. 제안한 방법은 원 영상으로부터 특징점을 검출하고, 클러스터 필터를 이용하여 유효한 특징점을 선별하고, 특징점 클러스터를 생성한다. 그리고 특징점 클러스터의 방향 각도를 이용하여 참조 객체를 선별하고, 분산 거리 비율을 이용하여 원 영상의 스케일을 예측한다. 예측한 스케일에 따라 참조 영상의 스케일을 변환하고, 변환된 참조 영상에 대해 특징점 검출을 적용한다. 실험 결과 제안한 방법은 다중 스케일 영상을 사용하는 SIFT 방법 및 Scaled ORB 방법에 비해 특징점 검출 시간이 각각 75% 및 71% 향상됨을 알 수 있었다.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 하계종합학술대회 논문집(4)
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• pp.238-241
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• 2000

A fingerprint core-point detection algorithm is presented in this paper. Core-point is useful for fingerprint classification and also for the fingerprint verification since it giver a reference to a fingerprint. Traditional methods of finding the core-point is introduced. These methods are the method using poincare index and the method using sine component of ridge directions. The proposed method is modified algorithm of the latter using the poincare index. The experimental results show that the proposed algorithm achieves almost the same accuracy with faster speed.

• 대한의용생체공학회:의공학회지
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• 제44권5호
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• pp.346-353
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• 2023

In this paper, we propose an innovative approach that leverages deep learning to find optimal reference points for achieving precise tooth segmentation in three-dimensional tooth point cloud data. A dataset consisting of 350 aligned maxillary and mandibular cloud data was used as input, and both end coordinates of individual teeth were used as correct answers. A two-dimensional image was created by projecting the rendered point cloud data along the Z-axis, where an image of individual teeth was created using an object detection algorithm. The proposed algorithm is designed by adding various modules to the Unet model that allow effective learning of a narrow range, and detects both end points of the tooth using the generated tooth image. In the evaluation using DSC, Euclid distance, and MAE as indicators, we achieved superior performance compared to other Unet-based models. In future research, we will develop an algorithm to find the reference point of the point cloud by back-projecting the reference point detected in the image in three dimensions, and based on this, we will develop an algorithm to divide the teeth individually in the point cloud through image processing techniques.