• International Journal of Fuzzy Logic and Intelligent Systems
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• 제13권4호
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• pp.284-290
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• 2013

Feature detection is very important to image processing area. In this paper we compare and analyze some characteristics of image processing algorithms for corner and blob feature detection. We also analyze the simulation results through image matching process. We show that how these algorithms work and how fast they execute. The simulation results are shown for helping us to select an algorithm or several algorithms extracting corner and blob feature.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1987년도 전기.전자공학 학술대회 논문집(I)
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• pp.86-89
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• 1987

In this paper, feature vectors composed of 6 features of Fourier spectrum of 2-D image at each projection angle and 7 features of invariant moments are defined. The feature are extracted by optical Fourier transformer and Radon transformer. After extracting the feature, the input pattern is recognized using the squared Mahalanobis distance.

• 한국정밀공학회지
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• 제27권1호
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• pp.64-75
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• 2010

This study introduces a complete feature map building method of sonar sensors for mobile robots. This method enhances the reality of feature maps by extracting even circle features as well as line and point features from sonar data. Edge features are, moreover, generated by combining line features close to circle features extracted around comer sites. The uncertainties of the specular reflection phenomenon and wide beam width of sonar data can be, therefore, reduced through this map building method. The experimental results demonstrate a practical validity of the proposed method in those environments.

• 전기학회논문지
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• 제67권10호
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• pp.1364-1369
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• 2018

Speech emotion recognition, which aims to classify speaker's emotional states through speech signals, is one of the essential tasks for making Human-machine interaction (HMI) more natural and realistic. Voice expressions are one of the main information channels in interpersonal communication. However, existing speech emotion recognition technology has not achieved satisfactory performances, probably because of the lack of effective emotion-related features. This paper provides a survey on various features used for speech emotional recognition and discusses which features or which combinations of the features are valuable and meaningful for the emotional recognition classification. The main aim of this paper is to discuss and compare various approaches used for feature extraction and to propose a basis for extracting useful features in order to improve SER performance.

• ETRI Journal
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• 제33권5호
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• pp.720-730
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• 2011

Opinion mining involves the analysis of customer opinions using product reviews and provides meaningful information including the polarity of the opinions. In opinion mining, feature extraction is important since the customers do not normally express their product opinions holistically but separately according to its individual features. However, previous research on feature-based opinion mining has not had good results due to drawbacks, such as selecting a feature considering only syntactical grammar information or treating features with similar meanings as different. To solve these problems, this paper proposes an enhanced feature extraction and refinement method called FEROM that effectively extracts correct features from review data by exploiting both grammatical properties and semantic characteristics of feature words and refines the features by recognizing and merging similar ones. A series of experiments performed on actual online review data demonstrated that FEROM is highly effective at extracting and refining features for analyzing customer review data and eventually contributes to accurate and functional opinion mining.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2002년도 ICCAS
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• pp.51.1-51
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• 2002

$\textbullet$ Introduction $\textbullet$ Vision-Based Motion Capture $\textbullet$ Extracting 2D features $\textbullet$ 3D Reconstruction $\textbullet$ UI for VR $\textbullet$ Conclusion

• 한국콘텐츠학회논문지
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• 제14권5호
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• pp.425-435
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• 2014

항공사진이나 위성영상으로부터 건물, 도로 등과 같은 인공지물을 추출하기 위한 연구가 활발히 수행되어 왔으며, 최근 수치항공사진의 해상도가 크게 개선됨에 따라 인공지물 추출 시 종종 원치 않는 잡영들이 검출되곤 한다. 본 연구에서는 이러한 잡영 문제를 보완하고 필요로 하는 대상물을 추출해 내기 위한 목적으로 알고리즘을 개발하였다. 이 알고리즘은 RGB영상의 채널을 분리하고 채널간의 차연산을 수행한 후 각 결과를 이진화하고 잡영제거 및 형태복원을 통하여 경계를 추출하도록 구성되었다. 경계 검출을 수행하기에 앞서 실험에 사용될 수치항공칼라사진에 대하여 광속조정, 수치지형모형 추출, 수치정사사진 생성 및 모자이크 작업 등의 사전처리 과정을 거쳤으며, 이렇게 하여 얻어진 수치정사사진 상에서 소형건물의 지붕경계를 본 연구에서 개발한 알고리즘을 사용하여 추출하였다. 또한 지붕경계 추출 결과를 종래의 방법으로 얻어진 결과와 비교함으로써 알고리즘의 타당성이 입증될 수 있었다.

• 전자공학회논문지B
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• 제33B권6호
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• pp.198-207
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• 1996

A PSRI (position, scale, and rotation invariant ) feature extraction and automatic target recognition system using a cooperative network and an MLP is proposed. We can extract position invarient features by obtaining the target center using the projection and the moment in preprocessing stage. The scale and rotation invariant features are extracted from the contour projection of the number of edge pixels on each of the concentric circles, which is input to the cooperative network. By extracting the representative PSRI features form the features and their differentiations using max-net and min-net, we can rdduce the number of input neurons of the MLP, and make the resulted automatic target recognition system less sensitive to input variances. Experiments are conduted on various complex images which are shifted, rotated, or scaled, and the results show that the proposed system is very efficient for PSRI feature extractions and automatic target recognitions.

• The Journal of the Acoustical Society of Korea
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• 제21권4E호
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• pp.156-163
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• 2002

We apply independent component analysis (ICA) for extracting an optimal basis to the problem of finding efficient features for representing speech signals of a given speaker The speech segments are assumed to be generated by a linear combination of the basis functions, thus the distribution of speech segments of a speaker is modeled by adapting the basis functions so that each source component is statistically independent. The learned basis functions are oriented and localized in both space and frequency, bearing a resemblance to Gabor wavelets. These features are speaker dependent characteristics and to assess their efficiency we performed speaker identification experiments and compared our results with the conventional Fourier-basis. Our results show that the proposed method is more efficient than the conventional Fourier-based features in that they can obtain a higher speaker identification rate.

• Journal of Information Processing Systems
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• 제14권2호
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• pp.523-538
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• 2018

Keystroke dynamics user authentication is a behavior-based authentication method which analyzes patterns in how a user enters passwords and PINs to authenticate the user. Even if a password or PIN is revealed to another user, it analyzes the input pattern to authenticate the user; hence, it can compensate for the drawbacks of knowledge-based (what you know) authentication. However, users' input patterns are not always fixed, and each user's touch method is different. Therefore, there are limitations to extracting the same features for all users to create a user's pattern and perform authentication. In this study, we perform experiments to examine the changes in user authentication performance when using feature vectors customized for each user versus using all features. User customized features show a mean improvement of over 6% in error equal rate, as compared to when all features are used.