A Study on Optimization Methods of X-Ray Machine Recognition for Aviation Security System
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Abstract
Traditional X-ray machine image recognition methods for airport security system have difficulties in recognition and are prone to result in recognition errors due to the impact of placing angle, density and volume of detected objects. This paper accurately describes the image features of X-ray machine visual image, carries out SVM classification after a visual dictionary is formed and enhances the accuracy of image discrimination by means of robust acceleration. The experimental results indicate that both identification efficiency and accuracy are improved to some extent.
DOI: https://doi.org/10.21307/ijssis-2017-808 | Journal eISSN: 1178-5608
Language: English
Page range: 1313 - 1332
Submitted on: Feb 25, 2015
Accepted on: Apr 30, 2015
Published on: Jun 1, 2015
Published by: Professor Subhas Chandra Mukhopadhyay
In partnership with: Paradigm Publishing Services
Publication frequency: 1 times per year
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© 2015 Ning Zhang, published by Professor Subhas Chandra Mukhopadhyay
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.