A rotation invariant template matching algorithm based on Sub-NCC

Abstract

This paper proposes an anti-rotation template matching method based on a portion of the whole pixels. To solve the problem that the speed of the original template matching method based on NCC (Normalized cross correlation) is too slow for the rotated image, a template matching method based on Sub-NCC is proposed, which improves the anti-jamming ability of the algorithm. At the same time, in order to improve the matching speed, the rotation invariant edge points are selected from the rotation invariant pixels, and the selected points are used for rough matching to quickly screen out the unmatched areas. The theoretical analysis and experimental results show that the accuracy of this method is more than 95%. For the search map at any angle with the resolution at the level of 300,000 pixel, after selecting the appropriate pyramid series and threshold, the matching time can be controlled to within 0.1 s.

Keywords

• machine vision
• template matching
• rotation invariance
• stable pixels
• normalized cross correlation