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X-ray imaging and CNN express parcel contraband detection method

A detection method and contraband technology, applied in image enhancement, image analysis, measuring devices, etc., can solve problems such as public safety impact, lack of professional knowledge of personnel, and complicated process

Pending Publication Date: 2020-07-31
ANHUI UNIV OF SCI & TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] With the development of the economy in recent years, the express delivery market has become more and more prosperous. The express delivery industry is a labor-intensive industry with long working hours and complicated processes.
Due to the lack of professional knowledge of the express business outlets, contraband may be received, causing unnecessary impact on economic and social development and public safety.

Method used

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  • X-ray imaging and CNN express parcel contraband detection method
  • X-ray imaging and CNN express parcel contraband detection method

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Embodiment Construction

[0018] In order to make the object, technical solution, and advantages of the present invention clearer, the present invention will be further described in detail below in conjunction with specific embodiments and with reference to the accompanying drawings.

[0019] The present invention works under Windows 10 environment, adopts Keras to analyze, and uses TensorFlow as its backend.

[0020] A kind of X-ray imaging and CNN express contraband detection method of the present invention comprises the following steps:

[0021] (1) Acquisition of package X-ray image information.

[0022] (2) Division of wrapped X-ray image samples.

[0023] (3) Feature extraction of packaged X-ray images.

[0024] (4) Construction of random forest contraband package recognition model.

[0025] In order to make the object, technical solution, and advantages of the present invention more clear, a kind of X-ray imaging and CNN express contraband detection method of the present invention will be des...

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Abstract

The invention discloses an X-ray imaging and CNN express parcel contraband detection method, and relates to the field of optical engineering and artificial intelligence, and the method comprises the following steps: (1) obtaining parcel X-ray image information; (2) dividing a wrapped X-ray image sample; (3) extracting features of the wrapped X-ray image; and (4) constructing a random forest contraband parcel identification model. According to the invention, the CNN-RF is adopted to construct an express parcel contraband detection model, a new convolutional neural network model is provided, more and more effective feature information can be extracted, over-fitting can be avoided, two GPUs are used for training, the training speed is greatly increased, and the method is very suitable for accurate and rapid detection of express parcel contraband goods.

Description

technical field [0001] The invention relates to the fields of optical engineering and artificial intelligence, and mainly relates to a detection method for express parcels containing contraband. Background technique [0002] With the development of the economy in recent years, the express delivery market has become increasingly prosperous. The express delivery industry is a labor-intensive industry with long working hours and complicated processes. Due to the lack of professional knowledge of the express business outlets, contraband may be received, causing unnecessary impact on economic and social development and public safety. [0003] Artificial intelligence (AI) is a new technical science that studies and develops theories, methods, technologies and application systems for simulating, extending and expanding human intelligence. It mainly includes robotics, image processing, natural language processing, expert systems, etc. Convolutional Neural Networks (CNN) is a type ...

Claims

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Application Information

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IPC IPC(8): G01N23/04G01V5/00G06T7/00
CPCG01N23/04G06T7/0002G06T2207/10116G06T2207/20081G06T2207/20084G01V5/22
Inventor 胡天羽徐双
Owner ANHUI UNIV OF SCI & TECH