• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.14 no.2
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• pp.202-208
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• 2003

In this paper, we proposed a microstrip patch array antenna for DBS reception which had high gain and high tilted angle through mutual coupling driver patch to parasitic patch in H-plane edge and broadside direction in different layers. It was designed and fabricated in 16$\times$8 array by using low cost polyester based copper-clad laminate and foam instead of high cost dielectric substrate. It had gain of 22.9 dBi, beamwidth of 4.6$^{\circ}$, and tilted angle from broadside direction of 43.9$^{\circ}$.

• Journal of Intelligence and Information Systems
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• v.8 no.1
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• pp.27-39
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• 2002

A locating text technique capable of locating and extracting text blocks in various Web images is presented here. Until now this area of work has been ignored by researchers even if this sort of text may be meaningful for internet users. The algorithms associated with the technique work without prior knowledge of the text orientation, size or font. In the work presented in this research, our text extraction algorithm utilizes useful edge detection followed by histogram analysis on the genuine characteristics of letters defined by text clustering region, to properly perform extraction of the text region that does not depend on font styles and sizes. By a number of experiments we have showed impressively acceptable results.

• Journal of Broadcast Engineering
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• v.23 no.3
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• pp.395-402
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• 2018

Human palms contain discriminative features for proving the identity of each person. In this paper, we present a novel method for user verification based on palmprints and palm veins. Specifically, the region of interest (ROI) is first determined to be forced to include the maximum amount of information with respect to underlying structures of a given palm image. The extracted ROI is subsequently enhanced by directional patterns and statistical characteristics of intensities. For multispectral palm images, each of convolutional neural networks (CNNs) is independently trained. In a spirit of ensemble, we finally combine network outputs to compute the probability of a given ROI image for determining the identity. Based on various experiments, we confirm that the proposed ensemble method is effective for user verification with palmprints and palm veins.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.41 no.6
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• pp.239-245
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• 2004

A hue-based noise-tolerant corner detector is proposed for the exact detection of the real corners in spite of the shadows and random noise. Based on the fact that the hue gradient at the border of the opaque objects' shadow is smaller than the intensity gradient in HSI (hue-saturation-intensity) color space, the effects of shadow are eliminated by introducing the hue-weighted combination of vector gradient to the proposed corner detector. Furthermore, the proposed corner detector is robust to random noise by offsetting the contribution to the corner candidate when the polarities of the color gradients of the pixel pairs are out of phase each other. Results of the experiment show that the proposed corner detector can effectively detect the real corners.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.419-423
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• 2008

사람의 손동작은 오랫동안 하나의 언어역할을 하는 통신 수단으로 사용되어 왔다. 이러한 손동작 중에서 가장 체계를 갖춘 수화는 청각장애인이 일반인과 일상 대화를 할 수 있도록 도와주는 주요한 통신 수단이다. 하지만 건청인들의 대부분이 습득하고 있지 않아 청각장애인들과 의사소통이 거의 불가능 한 것이 현실이다. 따라서 본 논문에서는 건청인과 청각장애인들 간의 의사소통을 원활하게 하기 위해 색상 정보와 퍼지 클러스터링 알고리즘을 이용한 실시간 수화 인식 방법을 제안한다. 제안된 방법은 화상 카메라를 통해 얻어진 실시간 영상에서 YCbCr 컬러 공간에서 색차 정보에 해당하는 Cb, Cr 정보를 각각 추출한 후, 이진화한 영상과 원본 영상에서 마스크를 통한 에지를 추출한 이진화 영상에 대해 논리연산을 통해 두 손의 위치와 외곽을 추출한다. 추출된 각 정보를 조합하여 8 방향 윤곽선 추적 알고리즘을 적용하여 객체의 위치를 추적한다. 그리고 추적한 객체의 영역에 대해 형태학적 정보를 이용하여 잡음을 제거한 후, 최종적으로 두 손의 영역을 추출한다. 추출된 손의 영역은 퍼지 클러스터링 기법 중의 FCM 알고리즘을 적용하여 수화의 특징들을 분류하고 인식한다. 제안된 방법의 성능을 평가하기 위해 화상카메라를 통해 얻어진 실시간 영상을 대상으로 실험한 결과, 제안된 방법이 두 손 영역의 추출에 효과적이고 수화 인식에 있어서 가능성을 확인하였다.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.10C
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• pp.1000-1009
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• 2007

This paper presents a content adaptive interpolation (CAI) for intra deinterlacing. The CAI consists of three steps: pre-processing, content classification, and adaptive interpolation. There are also three main interpolation methods in our proposed CAI, i.e. modified edge-based line averaging (M-ELA), gradient directed interpolation (GDI), and window matching method (WMM). Each proposed method shows different performances according to spatial local features. Therefore, we analyze the local region feature using the gradient detection and classify each missing pixel into four categories. And then, based on the classification result, a different do-interlacing algorithm is activated in order to obtain the best performance. Experimental results demonstrate that the CAI method performs better than previous techniques.

• Journal of Institute of Control, Robotics and Systems
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• v.21 no.8
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• pp.713-717
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• 2015

In this paper, we propose camber monitoring system which is using on hot rolling process. In roughing mill which is one of the rolling part in hot rolling process, steel plate can be bended in width direction under the imbalance of rolling condition. This bending of steel plate in width direction is called as camber. In order to measure the camber, first, cameras which are installed over transport pathway of steel plate take pictures of whole shape of steel plate. And location value of steel plate edge is extrated from these pictures by edge detection algorithm. But, there are a lot of noises which are generated by such as water sprays, dusts, peripheral equipments in these pictures, and these noises make edge detection difficult. In order to solve this kind of problem, we developed a direction selective edge detection algorithm, and applicated in our camber monitoring system. As a result, we got stable results in spite of process noises.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2814-2818
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• 2000

This paper describes an image processing algorithm capable of recognizing the road lane using a CDF (Cumulative Distribution Function). which is designed for the model function of the road lane. The CDF has distinctive peak points at the vicinity of the lane direction because of the directional and positional continuities of the lane. We construct a scatter diagram by collecting the edge pixels with the direction corresponding to the peak point of the CDF and carry out the principal axis-based line fitting for the scatter diagram to obtain the lane information. As noises play the role of making a lot of similar features to the lane appear and disappear in the image we introduce a recursive estimator of the function to reduce the noise effect and a scene understanding index (SUI) formulated by statistical parameters of the CDF to prevent a false alarm or miss detection. The proposed algorithm has been implemented in a real time on the video data obtained from a test vehicle driven in a typical highway.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.489-492
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• 2005

In this paper, we present a system for robust face detection based on wavelet transform using the standard models of image distortion. In the previous works, it was known to be difficult to treat a distorting of image information such as noises and light of the images obtained by a still camera and a movie camera. we analyze the high frequence information by using wavelet transform. This information is used for testing the image distortion and constructing the standard models of image distortion. The experimental results show that our extracting method based on standard models of image distortion is very effective.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06c
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• pp.341-343
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• 2012

본 논문에서는 기존의 특징점 기반 객체 인식 방법의 확장으로 보완적 특징점 기반의 컬러 정보를 포함하는 기술자를 활용하는 객체 인식 방법을 제안한다. 제안하는 방법은 무늬가 적은 객체에서도 에지의 위치를 샘플링함으로써 보완적 특징점을 생성해 낸다. 그리고 검출된 보완적 특징점으로부터 얻어지는 그레이 값 변화도방향 정보와 컬러 정보를 가지고 있는 기술자를 생성한다. 그리고 생성된 기술자를 객체 단위로 묶어 낼 수 있도록 하는 코드북(Codebook)을 학습함으로써 각 객체를 구분해 낼 수 있는 강건한 히스토그램를 생성한다. 생성된 코드북을 활용함으로써 제안하는 방법은 객체의 크기 및 환경 변화, 3차원 회전의 경우에도 기존의 방법보다 강건하게 인식한다. 실험 결과 제안하는 방법은 75.8% 인식률을 보이는 것을 확인하였다. 이 방법은 증강현실 응용에 정보 제시를 위해 가장 먼저 이루어지는 핵심 기술로써 활용될 수 있다.