메뉴 건너뛰기
.. 내서재 .. 알림
소속 기관/학교 인증
인증하면 논문, 학술자료 등을  무료로 열람할 수 있어요.
한국대학교, 누리자동차, 시립도서관 등 나의 기관을 확인해보세요
(국내 대학 90% 이상 구독 중)
로그인 회원가입 고객센터 ENG
주제분류

추천
검색
질문

논문 기본 정보

자료유형
학술저널
저자정보
Thang Duong Nhat (NAL Vietnam JSC) Binh Nguyen Duc (Hanoi University of Science and Technology) Phuong Le Khac (Hanoi University of Science and Technology) Ngoc Tu Nguyen (National Canter for Technological Progress) Mai Nguyen Thi Phuong (Hanoi University of Science and Technology)
저널정보
Korean Society for Precision Engineering Journal of the Korean Society for Precision Engineering Journal of the Korean Society for Precision Engineering Vol.36 No.8
발행연도
2019.8
수록면
683 - 690 (8page)
DOI
10.7736/KSPE.2019.36.8.683

이용수

표지
📌
연구주제
📖
연구배경
🔬
연구방법
🏆
연구결과
AI에게 요청하기
추천
검색
질문

초록· 키워드

오류제보하기
A planar-dimensions vision measurement method is proposed by developing a Neural Network to measure real-world distance between any two points on the plane. The system leveraging Neural Network ability to search in the solution space is a highly non-linear model that could map points’ location on the pixel plane of image(s) with the actual distance between them considering the non-uniform geometric distortion in captured images caused by the entocentric lens in a common camera. The method was tested with a printed calibration chessboard, placed in different locations on the plane, with measured distance between tested points. Experimental results show the proposed method’s mean absolute error is 1.24 × 10<SUP>-2</SUP> mm and standard deviation is 1.63 × 10<SUP>-3</SUP> mm, tested with 10-folds cross-validation method.

목차

1. Introduction
2. Method
3. Result and Discussion
REFERENCES

참고문헌 (26)

참고문헌 신청

함께 읽어보면 좋을 논문

논문 유사도에 따라 DBpia 가 추천하는 논문입니다. 함께 보면 좋을 연관 논문을 확인해보세요!

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2019-555-000936608