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논문 기본 정보
- 자료유형
- 학술대회자료
- 저자정보
- 저널정보
- Korean Institute of Information Scientists and Engineers 한국정보과학회 학술발표논문집 한국정보과학회 1995년도 봄 학술발표논문집 제22권 제1호
- 발행연도
- 1995.4
- 수록면
- 1,001 - 1,004 (4page)
이용수
초록· 키워드
오류제보하기
The classification of objects from the digitized images is one of the most important tasks of computer vision systems. In this paper, the new algorithm for pattern classification is described. It is based on the use of the signature and the autocorrelation which represent the shapes of boundaries detected in digitized binary images of the parts. And then Neural Network is applied for the pattern matching of parts. The autocorrelation representing the parts is invariant to the transformations like scaling, translation, and rotation of the image of parts. Also, the computation procedure of this algorithm is very simple. This algorithm could be applied to an accurate and fast recognition and inspection of parts in the automated manufacturing systems.
목차
ABSTRACT
1. 서론
2. 형상 정보 추출
3. 패턴 분류
4. 실험 및 결과
5. 결론
6. 참고문헌
참고문헌 (0)
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UCI(KEPA) : I410-ECN-0101-2009-569-017951830