Image Registration Using a Complete Polar Transform

ZHAO Wei; HUANG Lidong; WANG Jun; SUN Zebin

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Article Navigation > Chinese Journal of Electronics > 2014 > 23(2): 403-408

ZHAO Wei, HUANG Lidong, WANG Jun, et al., “Image Registration Using a Complete Polar Transform,” Chinese Journal of Electronics, vol. 23, no. 2, pp. 403-408, 2014,

Citation:

ZHAO Wei, HUANG Lidong, WANG Jun, et al., “Image Registration Using a Complete Polar Transform,” Chinese Journal of Electronics, vol. 23, no. 2, pp. 403-408, 2014,

ZHAO Wei, HUANG Lidong, WANG Jun, et al., “Image Registration Using a Complete Polar Transform,” Chinese Journal of Electronics, vol. 23, no. 2, pp. 403-408, 2014,

Citation:

ZHAO Wei, HUANG Lidong, WANG Jun, et al., “Image Registration Using a Complete Polar Transform,” Chinese Journal of Electronics, vol. 23, no. 2, pp. 403-408, 2014,

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Image Registration Using a Complete Polar Transform

Institute of Electronic and Information Engineering, Beihang University, Beijing 100191, China

Funds: This work is partly supported by National Natural Science Foundation of China-Royal Society of Edinburgh Joint Project: Next Generation Neurobiologically Inspired Autonomous Visual Surveillance Systems (No.61211130210).

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Corresponding author: ZHAO Wei
Received Date: 2013-04-01
Rev Recd Date: 2013-06-01
Publish Date: 2014-04-05

Abstract

Abstract

Image registration is widely used in image processing. Researchers have introduced image registration techniques based on the log-polar transform for its rotation and scale invariant properties. It suffers from nonuniform sampling which makes the registration results susceptible to interference. To address the problems of traditional log-polar transform, a Complete polar transform (CPT) method is proposed, which samples the image evenly to preserve the whole information of original image. An innovative projection transform is applied after CPT to obtain the rotation invariant property. We pre-matched feature points using the Scale invariant feature transform (SIFT)algorithm and re-matched them based onCPT to improve matching speed and accuracy. Experimental results show that the proposed method is accurate and robust to noise and alteration.
- Image registration,
- Polar transform,
- Feature points match,
- Scale invariant feature transform (SIFT)

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References(12)

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