Classification of X-Ray images of shipping containers

作者：

Highlights：

• Solving a real-world problem with an uncommon dataset.

• Highly time-efficient and accurate for classification of high resolution X-Ray images.

• Emphasizing on keypoints of the image instead of considering all parts of the image.

• Considering the dependency between the visual words in the bag of visual words.

• Adopting Tree-Augmented Bayes in the task of image classification.

摘要

•Solving a real-world problem with an uncommon dataset.•Highly time-efficient and accurate for classification of high resolution X-Ray images.•Emphasizing on keypoints of the image instead of considering all parts of the image.•Considering the dependency between the visual words in the bag of visual words.•Adopting Tree-Augmented Bayes in the task of image classification.

论文关键词：Shipping containers,Tree augmented naive Bayes (TAN),Bag of visual words (BOVW),Scale Invariant Feature Transform (SIFT)

论文评审过程：Received 6 April 2016, Revised 6 November 2016, Accepted 24 January 2017, Available online 31 January 2017, Version of Record 9 February 2017.

论文官网地址：https://doi.org/10.1016/j.eswa.2017.01.030