HUANG Min, MA Ya-qiong and GONG Qiu-ping. Image recognition based on improved Zernike moments[J]. Journal of Light Industry, 2013, 28(5): 66-69. doi: 10.3969/j.issn.2095-476X.2013.05.016
Citation:
HUANG Min, MA Ya-qiong and GONG Qiu-ping. Image recognition based on improved Zernike moments[J]. Journal of Light Industry, 2013, 28(5): 66-69.
doi:
10.3969/j.issn.2095-476X.2013.05.016
Image recognition based on improved Zernike moments
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College of Computer and Communication Engineering, Zhengzhou University of Light Industry, Zhengzhou 450001, China
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Received Date:
2013-08-21
Available Online:
2013-09-15
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Abstract
Aiming at the resampling and requantization error caused by image rotation and scaling transformation, the improved Zernike moment method was proposed, that is, first the target area in the image was normalized shapely, and then the Zernike moments were normalized. The experimental data showed that the improved Zernike moments not only had rotation invariance, but also had the scale invariance which didn't have before improved. The classification results of the target to be identified based on the minimum distance classifier showed that the improved Zernike moments had a higher recognition rate. Its shortcomings are not applicable to the complex situations of target image background.
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References
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Proportional views
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