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
Eung Sup Kim (Seoul National University) Hyuk-Jae Lee (Seoul National University)
저널정보
대한전자공학회 JOURNAL OF SEMICONDUCTOR TECHNOLOGY AND SCIENCE Journal of Semiconductor Technology and Science Vol.13 No.2
발행연도
2013.4
수록면
157 - 169 (13page)

이용수

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

초록· 키워드

오류제보하기
Scale Invariant Feature Transform (SIFT) generates image features widely used to match objects in different images. Previous work on hardware based SIFT implementation requires excessive internal memory and hardware logic [1]. In this paper, a new hardware organization is proposed to implement SIFT with less memory and hardware cost than the previous work. To this end, a parallel Gaussian filter bank is adopted to eliminate the buffers that store intermediate results because parallel operations allow all intermediate results available at the same time. Furthermore, the processing order is changed from the raster-scan order to the block-by-block order so that the line buffer size storing the source image is also reduced. These techniques trade the reduction of memory size with a slight increase of the execution time and external memory bandwidth. As a result, the memory size is reduced by 94.4%. The proposed hardware for SIFT implementation includes the Descriptor generation block, which is omitted in the previous work [1]. The addition of the hardwired descriptor generation improves the computation speed by about 30 times when compared with the previous work.

목차

Abstract
I. INTRODUCTION
II. SCALE-INVARIANT FEATURE TRANSFORM (SIFT)
III. ANALYSIS OF THE MEMORY REQUIREMENT BY THE PREVIOUS SIFT IMPLEMENTATION
IV. PROPOSED HARDWARE ARCHITECTURE WITH REDUCED MEMORY REQUIREMENT
V. HARDWARE ORGANIZATION FOR COST AND BANDWIDTH REDUCTIONS
VI. EVALUATION
VII. CONCLUSIONS
REFERENCES

참고문헌 (9)

참고문헌 신청

이 논문의 저자 정보

최근 본 자료

전체보기

댓글(0)

0

UCI(KEPA) : I410-ECN-0101-2014-560-003604944