A new distance measure based on generalized Image Normalized Cross-Correlation for robust video tracking and image recognition

Authors:
Arie Nakhmani;Allen Tannenbaum
Affiliations:
Department of Electrical and Computer Engineering, Boston University, Boston, MA, United States and Department of Electrical and Computer Engineering, UAB, Birmingham, AL, United States;Department of Electrical and Computer Engineering, UAB, Birmingham, AL, United States and Comprehensive Cancer Center, Department of Radiology, UAB, Birmingham, AL, United States
Venue:
Pattern Recognition Letters
Year:
2013

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Abstract

We propose two novel distance measures, normalized between 0 and 1, and based on Normalized Cross-Correlation for image matching. These distance measures explicitly utilize the fact that for natural images there is a high correlation between spatially close pixels. Image matching is used in various computer vision tasks, and the requirements to the distance measure are application dependent. Image recognition applications require more shift and rotation robust measures. In contrast, registration and tracking applications require better localization and noise tolerance. In this paper, we explore different advantages of our distance measures, and compare them to other popular measures, including Normalized Cross-Correlation (NCC) and Image Euclidean Distance (IMED). We show which of the proposed measures is more appropriate for tracking, and which is appropriate for image recognition tasks.