| 000 | nam k | |
| 001 | 2210080187086 | |
| 005 | 20140721131804 | |
| 007 | ta | |
| 008 | 940420s1993 bnka FB 000 kor | |
| 040 | ▼a221008 | |
| 041 | ▼akor▼beng | |
| 056 | ▼a530.969▼24 | |
| 100 | ▼a추광훈 | |
| 245 | 00 | ▼a部品形象 認識速度 向上을 위한 特徵點 檢出方法에 관한 硏究 /▼d秋侊勳 |
| 260 | ▼a부산:▼b東亞大學校 大學院,▼c1992 | |
| 300 | ▼a61 장:▼b삽도;▼c26 cm | |
| 502 | ▼a학위논문(석사)--▼b동아대학교 대학원:▼c산업공학과,▼d1992년 12월 | |
| 520 | ▼b영문초록 : In this paper, an alogrithm for edge detection and recognition system using contour tracing which relieved addition to constraint for the traditional pattern recognition system is proposed. This system consists of a preprocessing process, a feature extraction process, and a recognition process. The preprocessing process transfers source pattern in binary image and removes noise from the pattern image. The feature extraction process consists of thinning and edge detection activities. The thinning process is done by the Cheng-Hsu algorithm, however, the Laplacian edge detector is applied instead of the Cheng-Hsu for better performance. Edge is found by the proposed algorithm after the thinning process. Finally, the recognition process is followed using the edge parameter which is obtained at the thinning process. The process in this system is simple: so it extracts the direction codes of pattern contour very quick. | |
| 856 | ▼adonga.dcollection.net▼uhttp://donga.dcollection.net/jsp/common/DcLoOrgPer.jsp?sItemId=000002145184 | |
| 950 | ▼aFB | |
| 950 | ▼a비매품▼b￦3000▼c(추정가) |
部品形象 認識速度 向上을 위한 特徵點 檢出方法에 관한 硏究
종류
학위논문 동서
서명
部品形象 認識速度 向上을 위한 特徵點 檢出方法에 관한 硏究
저자명
발행사항
부산: 東亞大學校 大學院 1992
형태사항
61 장: 삽도; 26 cm
학위논문주기
학위논문(석사)-- 동아대학교 대학원: 산업공학과, 1992년 12월
주기사항
영문초록 : In this paper, an alogrithm for edge detection and recognition system using contour tracing which relieved addition to constraint for the traditional pattern recognition system is proposed. This system consists of a preprocessing process, a feature extraction process, and a recognition process. The preprocessing process transfers source pattern in binary image and removes noise from the pattern image. The feature extraction process consists of thinning and edge detection activities. The thinning process is done by the Cheng-Hsu algorithm, however, the Laplacian edge detector is applied instead of the Cheng-Hsu for better performance. Edge is found by the proposed algorithm after the thinning process. Finally, the recognition process is followed using the edge parameter which is obtained at the thinning process. The process in this system is simple: so it extracts the direction codes of pattern contour very quick.
관련 URL