Noise Control Boundary Image Matching Using Time-Series Moving Average Transform
Bum‐Soo Kim, Yang‐Sae Moon, Jinho Kim · 2009
To achieve the noise reduction effect in boundary image matching, we use the moving average transform of time-series matching. Our motivation is based on an intuition that using the moving average transform we may exploit the noise reduction effect in boundary image matching as in time-series matching. To confirm this simple intuition, we first propose -order image matching, which applies the moving average transform to boundary image matching. A boundary image can be represented as a sequence in the time-series domain, and our -order image matching identifies similar images in this time-series domain by comparing the -moving average transformed sequences. Next, we propose an index-based matching method that efficiently performs -order image matching on a large volume of image databases, and formally prove the correctness of the index-based method. Moreover, we formally analyze the relationship between an order and its matching result, and present a systematic way of controlling the noise reduction effect by changing the order . Experimental results show that our -order image matching exploits the noise reduction effect, and our index-based matching method outperforms the sequential scan by one or two orders of magnitude.