• 응용통계연구
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• 제26권1호
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• pp.131-139
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• 2013

지지벡터기계는 잡음변수가 존재하는 경우에 성능이 저하될 수 있다. 또한 최종 분류기에서 각 변수들의 중요도를 알리 어려운 단점이 있다. 따라서 변수선택은 지지벡터기계의 해석력과 정확도를 높일 수 있다. 기존의 문헌상의 대부분의 연구는 선형 지지벡터기계에서 성근 해를 주는 벌점함수를 통해 변수를 선택에 관한 것이다. 실제로는 분류의 정확도를 높이기 위해 비선형 커널을 사용하는 경우가 일반적이다. 따라서 변수선택은 비선형 지지벡터기계에서도 마찬가지로 필요하다. 본 논문에서는 모의실험 및 실제자료를 통하여 비선형 지지벡터의 대표적인 변수선택법인 COSSO(component selection and smoothing operator)와 KNIFE(kernel iterative feature extraction)의 성능을 비교한다.

• 대한전자공학회논문지
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• 제23권6호
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• pp.846-852
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• 1986

An efficient and reliable method for the extraction of features is presented. The method utilizes by a state technique with Euclidean distance operator. The proposed method is compared with the Sobel Operator. Simulation results show that our method performs as well as the Sobel operator.

• 한국측량학회:학술대회논문집
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• 한국측량학회 2003년도 춘계학술발표회 논문집
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• pp.181-185
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• 2003

Recently, in accordance with supplying high-resolution satellite images which as IKONOS, KVR-1000, and Quick Bird, the use of satellite images have increased in the study which extraction of features from high-resolution satellite images is becoming a new research focus. In this study, using generally involves such as image segmentation, filtering and sobel operator and thinning in image processing for extraction of feature from satellite image. We apply this method to extraction of feature which need to the revision of map from high-resolution IKONOS satellite image data, we verified the capability of extraction of feature and application using satellite image and proposed a plan for the study in the future.

• 한국측량학회지
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• 제13권2호
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• pp.299-307
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• 1995

본 논문은 수치영상으로부터 Digital Photogrammetry와 Computer Vision 분야에서 위치결정 및 3차원 정보의 자동추출을 위한 기본단계인 Distinct Point 추출기법중 F rsner interest operate에 관한 연구이다. Gradien에 기초한 Forstner interest operator는 Orientation-invariant의 특징을 가지고 있으며 소정의 Subpixel정확도를 얻을 수 있다. 본 연구에서는 Fostner interest operator에서 얻어진 Comer Points와 Circular Features를 구분하기 위한 방법으로 F-test를 적용하였으며 Nosie가 Forstner interest operator에 미치는 영향을 고찰하였고 실제 사진영상에 Forstner interest operator를 도입하여 실효성에 바탕을 둔 적용 여부를 검증하였다.

• Journal of Electrical Engineering and Technology
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• 제3권2호
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• pp.167-176
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• 2008

Vulnerability assessment of power systems is important so as to determine their ability to continue to provide service in case of any unforeseen catastrophic contingency such as power system component failures, communication system failures, human operator error, and natural calamity. An approach towards the development of on-line power system vulnerability assessment is by means of using an artificial neural network(ANN), which is being used successfully in many areas of power systems because of its ability to handle the fusion of multiple sources of data and information. An important consideration when applying ANN in power system vulnerability assessment is the proper selection and dimension reduction of training features. This paper aims to investigate the effect of using various feature extraction methods on the performance of ANN as well as to evaluate and compare the efficiency of the proposed feature extraction method named as neural network weight extraction. For assessing vulnerability of power systems, a vulnerability index based on power system loss is used and considered as the ANN output. To illustrate the effectiveness of ANN considering various feature extraction methods for vulnerability assessment on a large sized power system, it is verified on the IEEE 300-bus test system.

• 전기전자학회논문지
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• 제4권2호
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• pp.288-294
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• 2000

본 논문에서는 동영상 압축 기법을 향상시키기 위하여 효율적인 detail 추출 기법을 제안한다. 기존의 top-hat 변환을 이용한 기법은 고립되어 있고 시각적으로 중요한 detail의 추출에는 효율적이지만, 영역의 경계에서는 비효율적이다. 제안된 기법은 수리형태학적 Laplacian 연산의 영역경계 정보추출의 성질을 이용하여 압축을 향상시키고 저비트율을 제공한다. 실험결과를 통해서 제안된 기법이 기존 기법보다 효율적임을 보이고 수리형태학적 Laplacian 연산 적용의 타당성을 설명한다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2006년도 Proceedings of ISRS 2006 PORSEC Volume II
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• pp.643-646
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• 2006

This paper addresses the approach to extract linear features from satellite imagery using an efficient segmentation method. The extraction of linear features from satellite images has been the main concern of many scientists. There is a need to develop a more capable and cost effective method for the Iranian map revision tasks. The conventional approaches for producing, maintaining, and updating GIS map are time consuming and costly process. Hence, this research is intended to investigate how to obtain linear features from SPOT satellite imagery. This was accomplished using a discontinuity-based segmentation technique that encompasses four stages: low level bottom-up, middle level bottom-up, edge thinning and accuracy assessment. The first step is geometric correction and noise removal using suitable operator. The second step includes choosing the appropriate edge detection method, finding its proper threshold and designing the built-up image. The next step is implementing edge thinning method using mathematical morphology technique. Lastly, the geometric accuracy assessment task for feature extraction as well as an assessment for the built-up result has been carried out. Overall, this approach has been applied successfully for linear feature extraction from SPOT image.

• 한국정보처리학회논문지
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• 제6권3호
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• pp.821-831
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• 1999

3차운 물체 인식 중 오목과 볼록을 갖고 있는 물체의 인식은 대단히 어려운 문제이다. 본 논문에서는 물체의 인식을 위한 피처(Feature)의 추출 방법으로 오픈-볼(Open-Ball)을 제안한다. 이 새로운 방법은 물체의 크기, 이동고 회전에 불변성을 갖는 피처(Feature)를 생성하는 것뿐만이 아니라, 비교되는 물체를 인식하는 것을 상대적인 닮음 정도 측정으로 구현한다.

• 전자공학회논문지B
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• 제29B권10호
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• pp.90-99
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• 1992

In this paper, we propose a neural network model for speech recognition. The model consists of feature extraction parts and recognition parts. The interconnection model based on ${\Delta}^2$G operator was used for frequency analysis. Two features, global feature and local feature, were extracted from this model. Recognition parts consist of global grouping stage and local grouping stage. When the input pattern was coded by slope method, the recognition rate of speakers, A and B, was 100%. When the test was performed with the data of 9 speakers, the recognition rate of 91.4% was obtained.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2005년도 추계종합학술대회
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• pp.979-982
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• 2005

This paper is to be pre-processing that decides the text recognizability and quality contained in natural image. Differentiated with the existing studies, In this paper, it suggests the application of partially unified color models, Coiflet Wavelet and text extraction algorithm that uses the closed curve edge features of LoG (laplacian of gaussian)operator. The text image included in natural image such as signboard has the same hue, saturation and value, and there is a certain thickness as for their feature. Each color element is restructured into closed area by LoG operator, the 2nd differential operator. The text area is contracted by Hough Transform, logical AND-OR operator of each color model and Minimum-Distance classifier. This paper targets natural image into which text area is added regardless of the size and resolution of the image, and it is confirmed to have more excellent performance than other algorithms with many restrictions.