Computer Science – Computer Vision and Pattern Recognition
Scientific paper
2000-05-03
Computer Science
Computer Vision and Pattern Recognition
16 pages, Latex, 7 EPS figures, using esub2acm.cls and epsf.tex
Scientific paper
The paper has established and verified the theory prevailing widely among image and pattern recognition specialists that the bottom-up indirect regional matching process is the more stable and the more robust than the global matching process against concentrated types of noise represented by clutter, outlier or occlusion in the imagery. We have demonstrated this by analyzing the effect of concentrated noise on a typical decision making process of a simplified two candidate voting model where our theorem establishes the lower bounds to a critical breakdown point of election (or decision) result by the bottom-up matching process are greater than the exact bound of the global matching process implying that the former regional process is capable of accommodating a higher level of noise than the latter global process before the result of decision overturns. We present a convincing experimental verification supporting not only the theory by a white-black flag recognition problem in the presence of localized noise but also the validity of the conjecture by a facial recognition problem that the theorem remains valid for other decision making processes involving an important dimension-reducing transform such as principal component analysis or a Gabor transform.
Chen Liang
Tokuda Naoyuki
No associations
LandOfFree
Robustness of Regional Matching Scheme over Global Matching Scheme does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Robustness of Regional Matching Scheme over Global Matching Scheme, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Robustness of Regional Matching Scheme over Global Matching Scheme will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-230894