Earticle

초록

영어

The paper presents an algorithm which uses code vectors to represent comer geometry information for searching the similar images from a database. The comers have been extracted by finding the intersections of the detected lines found using Hough transform. Taking the comer as the center coordinate, the angles of the intersecting lines are determined and are represented using code vectors. A code book has been used to code each comer geometry information and indexes to the code book are generated. For similarity measurement, the histogram of the code book indexes is used. This result in a significant small size feature matrix compared to the algorithms using color features. Experimental results show that use of code vectors is computationally efficient in similarity measurement and the comers being noise invariant produce good results in noisy environments.

목차

Abstract
 I. Introduction
 II. Prior Work
 III. Proposed algorithm
 IV. Experimental results
 V. Performance Evaluation
 VI. Conclusion
 References

키워드

저자

• Ahmad Nishat [ 조선대학교 정보통신학과 박사수료 ] 주저자
• 조혜 [ Hui Zhao | 조선대학교 정보통신학과 석사과정 ] 공저자
• 박종안 [ Jong-An Park | 조선대학교 정보통신학과 교수 ] 공저자
• 박승진 [ Seung-Jin Park | 조선대학교 의공학과 교수 ] 교신저자
• 양원일 [ Won-II Yang | 조선대학교 전자공학과 교수 ] 교신저자

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국ITS학회논문지 [The Journal of The Korean Society of Intelligent Transport Systems]

• 간기

  격월간

• pISSN

  1738-0774

• eISSN

  2384-1729

• 수록기간

  2003~2026

• 등재여부

  KCI 등재

• 십진분류

  KDC 326 DDC 338