• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2000년도 제13회 신호처리 합동 학술대회 논문집
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• pp.901-904
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• 2000

A direct authentication from gray-scale image, instead of the conventional multi-step preprocessing, is proposed using Gabor filter-based features from the gray-scale fingerprint around core point. The core point is located as a reference point for the translation invariant matching. And its principal symmetry axis is detected for the rotation invariant matching from its neighboring region centered at the core point. And then fingerprint is divided into non-overlapping blocks with respect to the core point and features are directly extracted form the blocked gray level fingerprint using Gabor filter. The proposed fingerprint authentication is based on the Euclidean distance between the corresponding Gabor features of the input and the template fingerprints. Experiments are conducted on 300${\times}$300 fingerprints obtained from a CMOS sensor with 500 dpi resolution, and the proposed method could lower the False Reject Rate(FRR) to 18.2% under False Acceptance Rate(FAR) of 0%.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2008년도 하계종합학술대회
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• pp.987-988
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• 2008

In this paper, we propose a rotation invariant face detection method using Haar-like feature variation. Previous approaches using rectangular features can be calculated very fast. But rectangular features is weak in rotated face. Rotated Haar-like features can get high accuracy, but the performance is slow because it can't use the integral image. Our method vary Haar-like features keeping rectangular. this method makes the performance a bit slow, but gives better accuracy.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.55.5-55
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• 2001

The MST (Minimum Spanning Tree) matching algorithm had been used for searching the part accord points extracted from the gray level fingerprint image. The method, however, had some limitations. To obtain the relationship between enrolled and inputted fingerprint, the MST was used to generate the tree graph that represent the unique graph for given fingerprint data. From the graph, the accord points are estimated. However, the shape of the graph highly depends on the positions of the minutiae. If there are some pseudo minutiae caused by noise, the shape of the graph will be different In this paper, to overcome the limitations of the MST, we proposed CRM (Center of Rotation Method) algorithm that found the true part accord points. The proposed method is based on the assumption ...

• 대한방사선기술학회지:방사선기술과학
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• 제19권1호
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• pp.89-94
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• 1996

Misalignment between the electronic and mechanical axes of rotation will result in artifact generation and image degradation during single photon emission computed tomography(SPECT) reconstruction. Acceptance and quality control testing procedures have not emphasized the variability in center of rotation(COR) measurements caused by collimators and the need to verify uniformity across the full collimator field of view (FOV). Variation from the mean COR across the FOV was tested in four different collimators using multiple point source acquisitions. The mean COR was different for each collimator and one of the four had a > 0.5 pixel difference from the mean COR on some area of the FOV, This variation makes this collimator unacceptable for SPECT acquisition. Thus, initial acceptance testing of SPECT collimators should verify a uniform COR across the full FOV and collimators with a variability from the mean COR > 0.5 pixels should be rejected.

• 융합신호처리학회 학술대회논문집
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• 한국신호처리시스템학회 2001년도 하계 학술대회 논문집(KISPS SUMMER CONFERENCE 2001
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• pp.273-276
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• 2001

본 논문에서는 산업용으로 주로 사용되고 있는 바코드(code 73)글 비전시스템을 이용하여 자동으로 인식할 수 있는 알고리즘을 제안하였다. 제안된 알고리즘은 입력된 바코드 영상에 대해 회전에 관계없이 각도를 자동 추출하여, 모듈 (module)을 구성하는 화소들을 추출한다. 각 모듈에 대해 적응적인 방법으로 바(bar)와 스페이스(space)를 구성하는 엘리먼트(element) 값을 구하고, 심벌 문자들의 엘리먼트 값을 9개의 그룹으로 나누어 바코드 값을 인식한다. 여러 종류의 바코드 영상을 대상으로 모의실험을 수행하여, 제안한 알고리즘의 성능을 검증하였다.

• 전자공학회논문지B
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• 제32B권9호
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• pp.1171-1180
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• 1995

In this paper, we present a 3-D object recognition system in which the 3-D Hough transform domain is employed to represent the 3-D objects. In object modeling step, the features for recognition are extracted from the CAD models of objects to be recognized. Since the approach is based on the CAD models, the accuracy and flexibility are greatly improved. In matching stage, the sensed image is compared with the stored model, which is assumed to yield a distortion (location and orientation) in the 3-D Hough transform domain. The high dimensional (6-D) parameter space, which defines the distortion, is decomposed into the low dimensional space for an efficient recognition. At first we decompose the distortion parameter into the rotation parameter and the translation parameter, and the rotation parameter is further decomposed into the viewing direction and the rotational angle. Since we use the 3-D Hough transform domain of the input images directly, the sensitivity to the noise and the high computational complexity could be significantly alleviated. The results show that the proposed 3-D object recognition system provides a satisfactory performance on the real range images.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2007년도 하계종합학술대회 논문집
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• pp.385-386
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• 2007

In this paper, we present a detection method of facial angle using facial features. First, it finds face image using haar-like feature. After that, it finds eyes and lip in need of compute of face rotation angle. Next, it makes a triangle by using the facial features and computes the inside angle. As a result of experiment on various face images, the proposed method improves the efficiency much better than the conventional methods below $40^{\circ}$.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.255-262
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• 1998

This paper presents a translation, rotation and scale invariant methodology for the recognition of closed planar shape images using the bispectrum of a contour sequence and the learning vector quantization(LVQ) neural classifier. The contour sequences obtained from the closed planar images represent the Euclidean distance between the centroid and all boundary pixels of the shape, and are related to the overall shape of the images. The higher order spectra based on third order cumulants is applied to tihs contour sample to extract fifteen bispectral feature vectors for each planar image. There feature vector, which are invariant to shape translation, rotation and scale transformation, can be used to represent two0dimensional planar images and are fed into a neural network classifier. The LVQ architecture is chosen as a neural classifier because the network is easy and fast to train, the structure is relatively simple. The experimental recognition processes with eight different hapes of aircraft images are presented to illustrate the high performance of this proposed method even the target images are significantly corrupted by noise.

• 한국멀티미디어학회논문지
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• 제12권12호
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• pp.1728-1735
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• 2009

Human action tracking plays an important place in human-computer-interaction, human action tracking is a challenging task because of the exponentially increased computational complexity in terms of the degrees of freedom of the object and the severe image ambiguities incurred by frequent self-occlusions. In this paper, we will propose a novel method to track human action, in our technique, a dynamic background estimation algorithm will be applied firstly. Based on the estimated background, we then extract the human object from the video sequence, and the skeletonization method and Hough transform method will be used to detect the main structure of human body and each part rotation angle. The calculated rotation angles will be used to control a crane in the port, thus we can just control the container crane by using signalman body. And the experimental results can show that our proposed method can get a preferable result than the conventional methods such as: MIT, JPF or MFMC.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1996년도 Proceedings of the Korea Automatic Control Conference, 11th (KACC); Pohang, Korea; 24-26 Oct. 1996
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• pp.129-132
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• 1996

There is a tendency nowadays to produce increasingly miniaturized electronic equipment which incorporate parts that have to be precisely positioned, like lenses, heads and CCD's in scanners, printers, copiers, VCR's, optical fiber modules, etc. In contrast to the production process of precision parts, which is currently being carried out automatically, the assemblage process is still being performed by specially skilled technicians. The assemblage process comprises normally the following steps: firstly, the parts are roughly positioned and partially fixed, secondly, the parts are manually nudged towards the target position and finally glued, screwed or welded. This paper presents a system that uses six piezo Impact Drive Mechanisms for accurate micro positioning within three degrees of freedom (lateral and longitudinal translation and rotation). The system is designed to positioning a printed circuit board with an accuracy better than 3 .mu.m (for translations), 5 mrad (for rotation).