• International Journal of Quality Innovation
• /
• 제7권3호
• /
• pp.58-69
• /
• 2006

This paper presents neural network-based recognition system for automatic light emitting diode (LED) inspection. The back-propagation neural network (BPNN) is proposed and tested. The current-voltage (I-V) characteristic data of LED from the inspection process is used for the network training and testing. This study selects 300 random samples as network training and employs 100 samples as network testing. The experimental results show that if the classification work is done well, the accuracy of recognition is 100%, and the testing speed of the proposed recognition system is almost one half faster than the traditional inspection system does. The proposed neural-network approach is successfully demonstrated by real data sets and can be effectively developed as a recognition system for a practical application purpose.

• 한국산업융합학회 논문집
• /
• 제19권1호
• /
• pp.42-49
• /
• 2016

This study proposes a non-contact inspective technology based robot vision system for Faulty Inspection of welding States and Parts Shape. The maine focus is real time implementation of the machining parts' automatic inspection by the robotic moving. For this purpose, the automatic test instrument inspects the precision components designator the vision system. pattern Recognition Technologies and Precision Components for vision inspection technology and precision machining of precision parts including the status and appearance distinguish between good and bad. To perform a realization of a real-time automation integration system for the precision parts of manufacturing process, it is designed a robot vision system for the integrated system controller and verified the reliability through experiments. The main contents of this paper, the robot vision technology for noncontact inspection of precision components and machinery parts is useful technology for FA.

• 대한기계학회:학술대회논문집
• /
• 대한기계학회 2000년도 춘계학술대회논문집A
• /
• pp.542-547
• /
• 2000

In this paper, we propose a new approach to the development of the automatic vision system to examine and repair the steam generator tubes at remote distance. In nuclear power plants, workers are reluctant of works in steam generator because of the high radiation environment and limited working space. It is strongly recommended that the examination and maintenance works be done by an automatic system for the protection of the operator from the radiation exposure. Digital signal processors are used in implementing real time recognition and examination of steam generator tubes in the proposed vision system. Performance of proposed digital vision system is illustrated by simulation and experiment for similar steam generator model.

• 한국정밀공학회지
• /
• 제15권6호
• /
• pp.5-14
• /
• 1998

In this paper we propose a new approach to the development of the automatic vision system to examine and repair the steam generator tubes at remote distance. In nuclear power plants, workers are reluctant of works in steam generator because of the high radiation environment and limited working space. It is strongly recommended that the examination and maintenance works be done by an automatic system for the protection of the operator from the radiation exposure. Digital signal processors are used in implementing real time recognition and examination of steam generator tubes in the proposed vision system. Performance of proposed digital vision system is illustrated by simulation and experiment for similar steam generator model.

• 한국방송∙미디어공학회:학술대회논문집
• /
• 한국방송공학회 2015년도 하계학술대회
• /
• pp.516-517
• /
• 2015

The automatic traffic sign detection and recognition has been one of the highly researched and an important component of advanced driver assistance systems (ADAS). They are designed especially to warn the drivers of imminent dangers such as sharp curves, under construction zone, etc. This paper presents a traffic sign recognition (TSR) system using morphological operations and multiple descriptors. The TSR system is realized in three stages: segmentation, shape classification and recognition stage. The system is designed to attain maximum accuracy at the segmentation stage with the inclusion of morphological operations and boost the computation time at the shape classification stage using MB-LBP descriptor. The proposed system is tested on the German traffic sign recognition benchmark (GTSRB) and on Korean traffic sign dataset.

• 한국지능시스템학회논문지
• /
• 제16권2호
• /
• pp.240-246
• /
• 2006

This paper proposes the intelligent immigration control system that authorizes the traveler through immigration and detects forged passports by using automatic recognition of passport codes, the passport photo and face verification. The proposed system extracts and deskewes the areas of passport codes from the passport image. This paper proposes the novel ART algorithm creating the adaptive clusters to the variations of input patterns and it is applied to the extracted code areas for the code recognition. After compensating heuristically the recognition result, the detection of forged passports is achieved by using the picture and face verification between the passport photo extracted from the passport image and the picture retrieved from the database based on the recognized codes. Due to the proposed ART algorithm and the heuristic refinement, the proposed system relatively shows better performance.

• 한국컴퓨터정보학회논문지
• /
• 제12권3호
• /
• pp.37-50
• /
• 2007

본 논문에서는 캐리전파가 없어 고속연산이 가능한 잉여 수 체계(Residue Number System)를 이용하여 생산자동화 시스템에서 실시간 물체인식을 위한 고속의 디지털 뉴런 프로세서를 제안하고 이를 구현하기 위한 중요연산부인 PE를 설계 및 구현하였다. 설계된 디지털 뉴런프로세서는 잉여수계를 이용한 MAC(Multiplier and Accumulator)연산기와 혼합계수 변환을 이용한 시그모이드 함수 연산부로 구성된다. 설계된 회로는 C언어 및 VHDL로 기술하였고 Compass툴로 합성하였으며 LG $0.8{\mu}m$ CMOS공정으로 설계되었다. 실험결과 본 논문에서 설계 및 구현한 디지털 뉴런프로세서는 기존 방식의 잉여수계를 이용한 연산기 및 실수연산기로 구현한 뉴런프로세서에 비하여 3배 이상의 연산속도와 약 50%정도 하드웨어 크기를 줄일 수 있었다. 본 논문에서 설계 및 구현한 디지털 뉴런프로세서는 실시간 처리를 요하는 생산자동화 시스템의 물체인식 시스템에 적용될 수 있을 것으로 기대된다.

• 대한전자공학회:학술대회논문집
• /
• 대한전자공학회 2007년도 하계종합학술대회 논문집
• /
• pp.303-304
• /
• 2007

In this paper, we implement an automatic distance speech recognition system for voiced-enabled services. We first construct a baseline automatic speech recognition (ASR) system, where acoustic models are trained from speech utterances spoken by using a cross-talking microphone. In order to improve the performance of the baseline ASR using distance speech, the acoustic models are adapted to adjust the spectral characteristics of speech according to different microphones and the environmental mismatches between cross-talking and distance speech. Next we develop a voice activity detection algorithm for distance speech. We compare the performance of the base-line system and the developed ASR system on a task of PBW (Phonetically Balanced Word) 452. As a result it is shown that the developed ASR system provides the average word error rate (WER) reduction of 30.6 % compared to the baseline ASR system.

• 한국정밀공학회:학술대회논문집
• /
• 한국정밀공학회 1992년도 추계학술대회 논문집
• /
• pp.293-297
• /
• 1992

For the computerized monitoring and diagnosis of the undesirable chip chatter which are major obstacles to FMS, a pattern recognition system based on multi-layer perception neural network is developed and the performance of the system is experimentally evaluated. Experimental results show that recognition of the two class state of normal or abnormal cutting gives satisfactory results with success rate of 81`91%. Therefore, the proposed system has possibility for use in monitoring and diagnosis of automatic manufacturing system

• 한국산업정보학회논문지
• /
• 제12권3호
• /
• pp.60-68
• /
• 2007

본 논문에서는 자동으로 사용자의 얼굴 표정을 인식할 수 있는 시스템을 제안한다. 제안된 시스템은 휴리스틱 정보를 기반으로 설계된 트리 구조를 이용하여 행복, 역겨움, 놀람의 감정과 무표정을 인식한다. 카메라로부터 영상이 들어오면 먼저 얼굴 특징 검출기에서 피부색 모델과 연결성분 분석을 이용하여 얼굴 영역을 획득한다. 그 후에 신경망 기반의 텍스처 분류기를 사용하여 눈 영역과 비 눈 영역으로 구분한 뒤 눈의 중심 영역과 에지 정보를 기반으로 하여 눈, 눈썹, 입 등의 얼굴 특징을 찾는다. 검출된 얼굴 특징들은 얼굴 표정 인식기에 사용되며 얼굴 인식기는 이를 기반으로 한 decision tree를 이용하여 얼굴 감정을 인식한다. 제안된 방법의 성능을 평가하기 위해 MMI JAFFE, VAK DB에서 총 180장의 이미지를 사용하여 테스트하였고 약 93%의 정확도를 보였다.