• 전자공학회논문지B
• /
• 제30B권9호
• /
• pp.84-93
• /
• 1993

Recently, several nonlinear shape normalization methods have been proposed in order to compensate for the shape distortions in handwritten characters. In this paper, we review these nonlinear shape normalization methods from the two points of view : feature projection and feature density equalization. The former makes feature projection histogram by projecting a certain feature at each point of input image into horizontal-or vertical-axis and the latter equalizes the feature densities of input image by re-sampling the feature projection histogram. A systematic comparison of these methods has been made based on the following criteria: recognition rate, processing speed, computational complexity and measure of variation. Then, we present the result of quantitative evaluation of each method based on these criteria for a large variety of handwritten Hangul syllables.

• 대한음성학회지:말소리
• /
• 제46호
• /
• pp.37-50
• /
• 2003

In this paper, we evaluate and compare the performance of speech/music discrimination based on various feature parameters and classifiers. As for feature parameters, we consider High Zero Crossing Rate Ratio (HZCRR), Low Short Time Energy Ratio (LSTER), Spectral Flux (SF), Line Spectral Pair (LSP) distance, entropy and dynamism. We also examine three classifiers: k Nearest Neighbor (k-NN), Gaussian Mixure Model (GMM), and Hidden Markov Model (HMM). According to our experiments, LSP distance and phoneme-recognizer-based feature set (entropy and dunamism) show good performance, while performance differences due to different classifiers are not significant. When all the six feature parameters are employed, average speech/music discrimination accuracy up to 96.6% is achieved.

• 품질경영학회지
• /
• 제36권2호
• /
• pp.36-44
• /
• 2008

In this paper a novel feature extraction and selection is carried out in order to improve the discriminating capability between healthy and damaged structure using vibration signals. Although many feature extraction and selection algorithms have been proposed for vibration signals, most proposed approaches don't consider the discriminating ability of features since they are usually in unsupervised manner. We proposed a novel feature extraction and selection algorithm selecting few wavelet coefficients with higher class discriminating capability for damage detection and class visualization. We applied three class separability measures to evaluate the features, i.e. T test statistics, divergence, and Bhattacharyya distance. Experiments with vibration signals from truss structure demonstrate that class separabilities are significantly enhanced using our proposed algorithm compared to other two algorithms with original time-based features and Fourier-based ones.

• 대한원격탐사학회:학술대회논문집
• /
• 대한원격탐사학회 2005년도 Proceedings of ISRS 2005
• /
• pp.209-212
• /
• 2005

Hyperspectral data consists of more than 200 spectral bands that are highly correlated. In order to utilize hyperspectral data for classification, dimensional reduction or feature extraction is desired. By applying feature extraction, computational complexity of classification can be reduced and classification accuracy may be improved. In this paper, a genetic algorithm based feature extraction technique is proposed. Measure from discriminant analysis is utilized as optimization criterion. A subset of spectral bands is selected by genetic algorithm. Dimension of feature space is further reduced by linear transformation. Feasibility of the proposed technique is evaluated with AVIRIS data.

• 한국컴퓨터정보학회:학술대회논문집
• /
• 한국컴퓨터정보학회 2008년도 제39차 동계학술발표논문집 16권2호
• /
• pp.49-54
• /
• 2009

A fuzzy weighted mean method on a 2D shape recognition system is introduced in this paper. The bispectrum based on third order cumulant is applied to the contour sequence of each image for the extraction of a feature vector. This bispectral feature vector, which is invariant to shape translation, rotation and scale, represents a 2D planar image. However, to obtain the best performance, it should be considered certain criterion on the calculation of weights for the fuzzy weighted mean method. Therefore, a new method to calculate weights using means by differences of feature values and their variances with the maximum distance from differences of feature values. is developed. In the experiments, the recognition results with fifteen dimensional bispectral feature vectors, which are extracted from 11.808 aircraft images based on eight different styles of reference images, are compared and analyzed.

• 인지과학
• /
• 제15권1호
• /
• pp.25-33
• /
• 2004

본 논문은 자질기반 문법의 LR 파싱 테이블 생성과 관련된 두 가지 문제점을 논의한다. 먼저 자질기반 문법에 LR 파싱 방법을 적용할 경우 발생하는 비종결성 및 비결정성의 문제를 살펴본 후, 이 문제를 해결할 수 있는 LR 방법을 제시한다. 또한 파싱 테이블을 생성하기에는 충분한 정보를 가지지 못하는 하위명시 규칙의 문제점을 지적하고, 이러한 규칙들을 LR 파싱 방법으로 처리할 수 있도록 하는 규칙추론 알고리듬을 제안한다.

• 대한산업공학회지
• /
• 제41권4호
• /
• pp.338-343
• /
• 2015

We suggest a method to configure feature functions of continuous conditional random field (C-CRF). Regression tree and similarity analysis are introduced to construct the first and second feature functions of C-CRF, respectively. Rules from the regression tree are transformed to logic functions. If a logic in the set of rules is true for a data then it returns the corresponding value of leaf node and zero, otherwise. We build an Euclidean similarity matrix to define neighborhood, which constitute the second feature function. Using two feature functions, we make a C-CRF model and an illustrate example is provided.

• 한국항해항만학회:학술대회논문집
• /
• 한국항해항만학회 2016년도 춘계학술대회
• /
• pp.317-318
• /
• 2016

국제수로기구(IHO)는 수로분야의 다양한 데이터와 서비스 표준개발을 위한 프레임워크인 S-100 표준을 개발 하였으며, 이를 기반으로 차세대 전자해도 표준을 포함하는 제품 및 서비스 표준을 개발하고 있다. S-100 기반 제품표준을 개발하기 위해서는 S-100 표준에 부합하는 Feature Catalogue(FC)가 포함되어야 하며, 이를 지원하기 위해 S-100 Feature Catalogue Builder(FCB)가 개발 되었다. S-100 FCB를 이용하여, FC제작 시 Feature를 정의하기 위해서는 Attribute를 매번 입력 하게 되는데, 공통 Attribute를 입력함에 있어서의 입력 오류와 장시간의 제작 시간이 소요된다는 문제점이 발생한다. 이러한 문제점은 현 S-100 FCB가 객체지향 개념이 고려되지 못한 것으로 판단하고, 본 연구에서는 OOP(Object-Oriented Programming) 기반의 S-100 FCB 개발 방안을 연구하였다. 이를 통해 중복되는 정보의 입력을 줄이고 제작 시간을 단축 할 수 있을 것으로 예상된다.

• 대한기계학회논문집
• /
• 제17권10호
• /
• pp.2446-2456
• /
• 1993

By virtue of progress of computer science, CAD/CAM technology has been developed greatly in each area. But the problems in the integration of CAD/CAM are not yet solved completely. The reason is that the exchange of data between CAD and CAM is difficult because the domains of design and manufacturing are different in nature. To solve this problem, a feature based modeller is developed in this study, which makes it possible to communicate between design and manufacturing through features. The modeller has feature, the concept of semi-bounded plane is introduced, and implemented as a B-rep sheet model using half-edge data structure. The features are then created on a part by local modification of the boundary on a part based on feature template information. This approach generalizes the modelling of features in a geometry model.

• 로봇학회논문지
• /
• 제15권1호
• /
• pp.1-7
• /
• 2020

In this paper, we introduce the methodology that utilizes deep learning-based front-end to enhance underwater feature matching. Both optical camera and sonar are widely applicable sensors in underwater research, however, each sensor has its own weaknesses, such as light condition and turbidity for the optic camera, and noise for sonar. To overcome the problems, we proposed the opti-acoustic transformation method. Since feature detection in sonar image is challenging, we converted the sonar image to an optic style image. Maintaining the main contents in the sonar image, CNN-based style transfer method changed the style of the image that facilitates feature detection. Finally, we verified our result using cosine similarity comparison and feature matching against the original optic image.