Occluded Shape Matching for Image Database of Reduced Data Points

• 영문명: Occluded Shape Matching for Image Database of Reduced Data Points
• 발행기관: 한국과학기술원 인간친화 복지 로봇 시스템 연구센터
• 저자명: Md. Jahangir Alam Hiromitsu Hama
• 간행물 정보: 『International Journal of Assistive Robotics and Mechatronics』International Journal of Human-friendly Welfare Robotic Systems Vol.4 No.4, 27~36쪽, 전체 10쪽
• 주제분류: 공학 > 제어계측공학
• 파일형태: PDF
• 발행일자: 2003.12.01

영문 초록

  We present a new approach to typify object contours in a database by a reduced number of data points and to match object shapes in occluded conditions. For simplicity, contours are approximated by a set of quadratic Bezier curves and all control points are stored in the database. Initial contour segmentation procedure is carried out based on scale space parameters. The scale is chosen imposing the condition that a particular number of curvature zero-crossing points survive on the object contour for a longer period of its changes. Its value is neither too small nor too large so that the influence of noise effects and the loss of important features can be avoided. We introduce the distance matrix, which is constructed from curve to curve distance measurement between the test and database contours. The maximum alignment of distance matrix elements for their verification gives the total cost of similarity between the test and database contours. We present the experimental results to confirm the effectiveness of the proposed method and demonstrate the successful performance on object contours containing noise and occlusion.

목차

Abstract
Ⅰ. INTRODUCTION
Ⅱ. FEATURE SELECTON FOR DATABASE
Ⅲ. CONTOUR DISTANCE MEASUREMENT
Ⅳ. CURVE PAIR SIMILARITY
Ⅴ. EXPERIMENTAL RESULTS
Ⅵ. CONCLUSION
REFERENCES

키워드

Bezier curves control points database scale space parameters curvature zero？crossing points distance matrix