• International Journal of Contents
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• 제13권4호
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• pp.70-79
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• 2017

Images are an important element in patents and many experts use images to analyze a patent or to check differences between patents. However, there is little research on image analysis for patents partly because image processing is an advanced technology and typically patent images consist of visual parts as well as of text and numbers. This study suggests two methods for using image processing; the Scale Invariant Feature Transform(SIFT) algorithm and Optical Character Recognition(OCR). The first method which works with SIFT uses image feature points. Through feature matching, it can be applied to calculate the similarity between documents containing these images. And in the second method, OCR is used to extract text from the images. By using numbers which are extracted from an image, it is possible to extract the corresponding related text within the text passages. Subsequently, document similarity can be calculated based on the extracted text. Through comparing the suggested methods and an existing method based only on text for calculating the similarity, the feasibility is achieved. Additionally, the correlation between both the similarity measures is low which shows that they capture different aspects of the patent content.

• 한국컴퓨터정보학회논문지
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• 제11권3호
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• pp.133-139
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• 2006

컴퓨터 정보기술의 발달로 멀티미디어 데이터가 급증하고 있다. 특히, 영상검색 분야에서는 영상 데이터의 신속, 정확한 처리 및 분석이 요구된다. 그러나 일반적으로 신속성과 정확성을 모두 보장하는 데는 어려움이 있다. 본 논문은 이러한 문제를 해결하기 위하여 유전자 알고리즘을 이용해 영상의 대표 특징치를 추출하는 알고리즘을 제안한다. 이 알고리즘은 영상이 가지고 있는 대표적인 특징치 뽑아냄으로써 검색의 신속성과 정확성을 보장한다. 영상의 특징으로는 색상과 질감을 사용하였다. 실험결과, 기존의 연구에 비해 제안된 특징 추출법이 더 좋은 정확성을 보임으로서 제안된 방법의 타당성을 입증하였다.

• 한국전기전자재료학회논문지
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• 제20권1호
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• pp.65-73
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• 2007

Pattern classification of single and multiple discharge sources was applied using a wavelet image signal method in which a feature extraction was applied using a hidden sub-image. A feature extracting method that used vertical and horizontal images using an MSD method was applied to an averaging process for the scale of pulses for the phase. A feature extracting process for the preprocessing of the input of a neural network was performed using an inverse transformation of the horizontal, vertical, and diagonal sub-images. A back propagation algorithm in a neural network was used to classify defective signals. An algorithm for wavelet image processing was developed. In addition, the defective signal was classified using the extracted value that was quantified for the input of a neural network.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 학술대회 논문집 정보 및 제어부문
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• pp.517-519
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• 2004

This paper describes an approach to estimate a robot pose with an image. The algorithm of pose estimation with an image can be broken down into three stages : extracting scale-invariant features, matching these features and calculating affine invariant. In the first step, the robot mounted mono camera captures environment image. Then feature extraction is executed in a captured image. These extracted features are recorded in a database. In the matching stage, a Random Sample Consensus(RANSAC) method is employed to match these features. After matching these features, the robot pose is estimated with positions of features by calculating affine invariant. This algorithm is implemented and demonstrated by Matlab program.

• 한국산업융합학회 논문집
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• 제23권3호
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• pp.515-521
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• 2020

Deep learning methods have been effectively used to provide great improvement in various research fields such as machine learning, image processing and computer vision. One of the most frequently used deep learning methods in image processing is the convolutional neural networks. Compared to the traditional artificial neural networks, convolutional neural networks do not use the predefined kernels, but instead they learn data specific kernels. This property makes them to be used as feature extractors as well. In this study, we compared the quality of CNN features for traditional texture feature extraction methods. Experimental results demonstrate the superiority of the CNN features. Additionally, the recognition process and result of a pioneering CNN on MNIST database are presented.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2005년도 ICCAS
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• pp.2373-2378
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• 2005

An emotion detection algorithm using frontal facial image is presented in this paper. The algorithm is composed of three main stages: image processing stage and facial feature extraction stage, and emotion detection stage. In image processing stage, the face region and facial component is extracted by using fuzzy color filter, virtual face model, and histogram analysis method. The features for emotion detection are extracted from facial component in facial feature extraction stage. In emotion detection stage, the fuzzy classifier is adopted to recognize emotion from extracted features. It is shown by experiment results that the proposed algorithm can detect emotion well.

• 대한전기학회논문지:전력기술부문A
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• 제48권10호
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• pp.1311-1316
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• 1999

A visual servoing method has been proposed based on disturbance observer to eliminate the effect of the off-diagonal component of image feature Jacobian, since performance indices such as measurement sensitivity of visual features, sensitivity of the control to noise and controllability could be improved when an image feature Jacobian was given as a block diagonal matrix. In this paper, experimental results of disturbance observer-based visual servoing are discussed where Samsung FARAMAN-AS1 6-axis industrial robot manipulator is employed. Also, the feature saturator is proposed to stabilize the disturbance observer loop by saturating the differential changes of the image features.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.9-11
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• 2005

We propose a new content-based image retrieval using a block color co-occurrence matrix (BCCM) and pattern correlogram. In the proposed method, the color feature vectors are extracted by using BCCM that represents the probability of the co-occurrence of two mean colors within blocks. Also the pattern feature vectors are extracted by using pattern correlogram which is combined with spatial correlation of pattern. In the proposed pattern correlogram method. after block-divided image is classified into 48 patterns with respect to the change of the RGB color of the image, joint probability between the same pattern from the surrounding blocks existing at the fixed distance and the center pattern is calculated. Experimental results show that the proposed method can outperform the conventional methods as regards the precision and the size of the feature vector dimension.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
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• pp.61-63
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• 2005

Retreiving indoor scene reference image from database using visual information is important issue in Robot Navigation. Scene matching problem in navigation robot is not easy because input image that is taken in navigation process is affinly distorted. We represent probabilistic framework for the feature matching between features in input image and features in database reference images to guarantee robust scene matching efficiency. By reconstructing probabilistic scene matching framework we get a higher precision than the existing feaure-feature matching scheme. To construct probabilistic framework we represent each image as Gaussian Mixture Model using Expectation Maximization algorithm using SIFT(Scale Invariant Feature Transform).

• Journal of Electrical Engineering and Technology
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• 제8권2호
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• pp.385-392
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• 2013

An uncalibrated visual servo control method for tracking a target is presented. We define the robot-positioning problem as an unconstrained optimization problem to minimize the image error between the target feature and the robot end-effector feature. We propose a method to find the residual term for more precise modeling using the secant approximation method. The composite image Jacobian is estimated by the proper method for eye-to-hand configuration without knowledge of the kinematic structure, imaging geometry and intrinsic parameter of camera. This method is independent of the motion of a target feature. The algorithm for regulation of the joint velocity for safety and stability is presented using the cost function. Adaptive regulation for visibility constraints is proposed using the adaptive parameter.