• KSII Transactions on Internet and Information Systems (TIIS)
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• 제13권4호
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• pp.2078-2093
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• 2019

Visual smoke recognition is a challenging task due to large variations in shape, texture and color of smoke. To improve performance, we propose a novel smoke recognition method by combining dual-encoded features that are extracted from both spatial and Curvelet domains. A Curvelet transform is used to filter an image to generate fifty sub-images of Curvelet coefficients. Then we extract Local Binary Pattern (LBP) maps from these coefficient maps and aggregate histograms of these LBP maps to produce a histogram map. Afterwards, we encode the histogram map again to generate Dual-encoded Local Binary Patterns (Dual-LBP). Histograms of Dual-LBPs from Curvelet domain and Completed Local Binary Patterns (CLBP) from spatial domain are concatenated to form the feature for smoke recognition. Finally, we adopt Gaussian Kernel Optimization (GKO) algorithm to search the optimal kernel parameters of Support Vector Machine (SVM) for further improvement of classification accuracy. Experimental results demonstrate that our method can extract effective and reasonable features of smoke images, and achieve good classification accuracy.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2005년도 추계학술대회 및 정기총회
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• pp.175-181
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• 2005

This paper describes the development of on-line computer vision laboratories to teach the detailed image processing and pattern recognition techniques. The computer vision laboratories include distant image acquisition method, basic image processing and pattern recognition methods, lens and light, and communication. This study introduces a case study that teaches computer vision in distance learning environment. It shows a schematic of a distant loaming workstation and contents of laboratories with image processing examples. The study focus more on the contents of the vision Labs rather than internet application method. The study proposes the ways to improve the on-line computer vision laboratories and includes the further research perspectives

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2012년도 추계학술대회 논문집
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• pp.419-420
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• 2012

• 한국산업정보학회논문지
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• 제22권6호
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• pp.39-45
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• 2017

기존의 색상기반 얼굴인식 방법은 조명변화에 민감하며, 위변조의 가능성이 있기 때문에 다양한 산업분야에 적용되기 어려운 문제가 있었다. 본 논문에서는 이러한 문제를 해결하기 위해 깊이 영상을 이용한 지역 이진 패턴(LBP) 기반의 얼굴인식 방법을 제안한다. 깊이 정보를 이용한 얼굴 검출 방법과 얼굴 인식을 위한 특징 추출 및 매칭 방법을 구현하고, 모의실험 결과를 바탕으로 제안된 방식의 인식 성능을 나타낸다.

• 한국멀티미디어학회논문지
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• 제24권8호
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• pp.1012-1019
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• 2021

Currently, since the black-white QR (Quick Response) codes have limited storage capacity, color QR codes have been actively being studied. By multiplexing 3 colors, the color QR codes can allow the code capacity to be increased by three times, however, the color multiplexing brings about the possibility of crosstalk and noises in the acquisition process of the final image, incurring the decrease of bit-recognition rate. In order to improve the bit recognition rate, while keeping the storage capacity high, this paper proposes a new type of color QR code which uses the pattern information as well as the color information, and then analyzes how to increase the bit recognition rate. For this aim, the paper presents an efficient system which extracts embedded information from color QR code and then, through practical experiments, it is shown that the proposed color QR codes improves the bit recognition rate and are useful for commercial applications, compared to the conventional color codes.

• 한국통신학회논문지
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• 제37C권10호
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• pp.925-932
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• 2012

본 논문에서는 패턴 인식 알고리즘을 기반으로 인간 형태를 가진 휴머노이드 로봇의 보행 동작을 제어하는 경로 인식 시스템을 개발하였다. 휴머노이드 로봇이 효과적인 작업 수행을 할 수 있도록 행동 프리미티브를 정의 하였으며, Canny 에지 검출 알고리즘을 적용한 보도 블록의 패턴 및 색상 추출, 이를 기반으로 한 이동 방향을 인식하는 알고리즘 제안하고, 리눅스 운영체제와 영상 카메라가 장착된 소형 휴머노이드 임베디드 시스템에 구현하였다. 제안 알고리즘의 성능 실험을 휴머노이드 로봇의 동작 속도 및 인식율에 관점에서 수행하였으며, 다양한 현실 환경을 반영하기 위해 경사도 및 조도 변화를 적용하였다. 실험 결과 제안 알고리즘은 다양한 환경에서 시각 장애인의 길안내 도우미 로봇으로서 적절한 수준에서 반응함을 확인하였다.

• 한국통신학회논문지
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• 제28권5C호
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• pp.486-492
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• 2003

퍼지 ART 알고리즘에서 경계 변수는 임의의 패턴과 저장된 패턴과의 불일치(mismatch) 허용도를 결정한다. 이 경계 변수가 크면 입력 패턴과 저장 패턴 사이에 약간의 차이가 있어도 새로운 카테고리(category)로 분류하게 된다. 반대로 경계 변수가 작으면 입력 패턴과 저장 패턴 사이에 많은 차이가 있더라도 유사성이 인정되어 입력 패턴을 저장 패턴의 카테고리로 분류한다. 따라서 영상 인식에 적용하기 위해서는 경계 변수를 경험적으로 설정한다. 그리고 연결 가중치를 조정하는 과정에서 저장된 패턴들의 정보들이 손실되는 경우가 발생하여 인식률을 저하시킨다. 본 논문에서는 퍼지 ART 알고리즘의 문제점을 개선하기 위하여 퍼지 논리 접속 연산자를 이용하여 경계 변수를 동적으로 조정하고 저장 패턴과 학습 패턴간의 실제적인 왜곡 정도를 충분히 고려하여 승자 노드로 선택된 빈도수를 가중치 조정에 적용하는 개선된 퍼지 ART 알고리즘을 제안하였다. 제안된 방법의 인식 성능을 확인하기 위해서 운송 컨테이너 영상을 대상으로 실험한 결과, 기존의 ART2 알고리즘이나 퍼지 ART 알고리즘보다 클러스터의 수가 적게 생성되었고 인식 성능도 기존의 방법들보다 우수한 성능이 있음을 확인하였다.

• 전기학회논문지P
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• 제52권1호
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• pp.35-41
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• 2003

In this paper, a machine vision system for recognizing and classifying the patterns and marks engraved by die molding or laser marking on the glass panels of computer monitors is suggested and evaluated experimentally. The vision system is equipped with a neural network and an NGC pattern classifier including searching process based on normalized grayscale correlation and adaptive binarization. This system is found to be applicable even to the cases in which the segmentation of the pattern area from the background using ordinary blob coloring technique is quite difficult. The inspection process is accomplished by the use of the NGC hypothesis and ANN verification. The proposed pattern recognition system is composed of three parts: NGC matching process and the preprocessing unit for acquiring the best quality of binary image data, a neural network-based recognition algorithm, and the learning algorithm for the neural network. Another contribution of this paper is the method of generating the training patterns from only a few typical product samples in place of real images of all types of good products.

• 한국공작기계학회:학술대회논문집
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• 한국공작기계학회 2000년도 춘계학술대회논문집 - 한국공작기계학회
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• pp.585-590
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• 2000

Recently, It is gradually raised necessity that thickness of thin film is measured accuracy and managed in industrial circles and medical world. Ultrasonic Signal processing method is likely to become a very powerful method for NDE method of detection of microdefects and thickness measurement of thin film below the limit of Ultrasonic distance resolution in the opaque materials, provides useful information that cannot be obtained by a conventional measuring system. In the present research, considering a thin film below the limit of ultrasonic distance resolution sandwiched between three substances as acoustical analysis model, demonstrated the usefulness of ultrasonic Signal processing technique using information of ultrasonic frequency for NDE of measurements of thin film thickness, sound velocity, and step height, regardless of interference phenomenon. Numeral information was deduced and quantified effective information from the image. Also, pattern recognition of a defected input image was performed by neural network algorithm. Input pattern of various numeral was composed combinationally, and then, it was studied by neural network. Furthermore, possibility of pattern recognition was confirmed on artifical defected input data formed by simulation. Finally, application on unknown input pattern was also examined.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1988년도 전기.전자공학 학술대회 논문집
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• pp.687-690
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• 1988

Algorithms that represent given pattern in the form of an ARG (Attributed relational graph) using not only structural relations but also symbolic or numerical attributes, and then recognize that pattern by graph matching process are presented in this paper. Based on definitions of pattern deformational models, algorithms that can find GPECI(Graph preserved error correcting isomorphism). SGECI(subgraph ECI) and DSECI(Double subgraph ECI) are proposed and comparisons among these algorithms are described. To be useful in performig practical tasks, efficient schemes for extraction of ARG representation fron raw image are needed. In this study, given patterns are restricted within objects having distinct skeleton, and then the information which is necessary for recognition and analysis is successfully extracted.