Vehicle identification methods and systems

US10607483B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-10607483-B2
Application numberUS-201515300947-A
CountryUS
Kind codeB2
Filing dateDec 23, 2015
Priority dateDec 30, 2014
Publication dateMar 31, 2020
Grant dateMar 31, 2020

How to read this patent

A practical reading order for non-experts. Skip the full description unless you need deep technical detail.

  1. Title

    What the patent document calls the invention.

  2. Abstract

    A short plain-language summary of the technical disclosure.

  3. Assignees and inventors

    Who owns or filed the patent and who is credited as inventor.

  4. Key dates

    Filing, priority, publication, and grant dates set the timeline.

  5. First independent claim

    The legal scope of protection — read this for what is actually claimed.

  6. CPC / IPC classifications

    Technology tags used to group this patent with similar filings.

  7. Citations and related patents

    Prior art links and similar publications in this corpus.

Abstract

Official abstract text for this publication.

Disclosed is a vehicle identification method and system. The method includes: acquiring appearance information of an inspected vehicle; obtaining external features of the vehicle based on the appearance information; acquiring a transmission image of the vehicle and obtaining internal features of the vehicle from the transmission image; forming descriptions on the vehicle at least based on the external features and the internal features; and determining a vehicle model of the vehicle from a vehicle model databased by utilizing the descriptions. This method merges various types of modality information, especially introducing the transmission image, and combines the internal structure information with the appearance information, so that the present disclosure can identify a vehicle model more practically.

First claim

Opening claim text (preview).

We claim: 1. A vehicle identification method comprising: acquiring appearance information of an inspected vehicle and obtaining external features of the vehicle based on the appearance information; acquiring an X-ray image of the vehicle and obtaining internal features of the vehicle from the X-ray image; forming descriptions on the vehicle based on the external features and the internal features; and determining a vehicle model of the vehicle from a vehicle model database by utilizing the descriptions, wherein the appearance information includes contour information obtained by using an infrared sensor, and face information and chassis information of the vehicle obtained using a visible light sensor, and wherein the external features include contour features based on the contour information, face features based on the face information, and chassis features based on the chassis information, wherein the contour features, the face features, the chassis features, and internal features are respectively extracted based on characteristics of modalities thereof, and wherein the vehicle is identified by first using the contour features, the face features, the chassis features, and internal features in a sequential form to improve an identification rate of the vehicle model of the vehicle. 2. The method according to claim 1 , wherein said obtaining internal features of the vehicle from the X-ray image comprises: dividing the X-ray image into a plurality of sub-image blocks; performing feature extraction on the plurality of sub-image blocks; and performing significance weighting on features of each sub-image block to form the internal features of the vehicle. 3. The method according to claim 2 , wherein the vehicle's head has significance larger than that of the vehicle's side. 4. The method according to claim 2 , wherein a bag-of-word model based feature extraction is performed on the plurality of sub-image blocks, and local significance weighting is performed on the extracted bag-of-word model features to form perspective features by means of concatenation or direct summation. 5. The method according to claim 1 , wherein a gradient operation is applied on the chassis image to form a gradient image, and then local projection features of the gradient image are used as the chassis features. 6. The method according to claim 5 , wherein the gradient image is divided into a plurality of sub-image blocks, and a horizontal projection, a vertical projection and/or a slanting projection of the sub-image blocks are calculated, respectively, to form feature vectors as the chassis features. 7. A vehicle identification system comprising: a sensor configured to sense appearance information of an inspected vehicle; a ray scanning device configured to perform ray scanning on the inspected vehicle to acquire an X-ray image of the vehicle; and an information processing device configured to obtain external features of the vehicle based on the appearance information, to obtain internal features of the vehicle from the X-ray image, to form descriptions on the vehicle based on the external features and the internal features, and to determine a vehicle model of the vehicle from a vehicle model database by utilizing the descriptions, wherein the appearance information includes contour information obtained by using an infrared sensor, and face information and chassis information of the vehicle obtained using a visible light sensor, and wherein the external features include contour features based on the contour information, face features based on the face information and chassis features based on the chassis information, wherein the contour features, the face features, the chassis features, and internal features are respectively extracted based on characteristics of modalities thereof, and wherein the vehicle is identified by first using the contour features, the face features, the chassis features, and internal features in a sequential form to improve an identification rate of the vehicle model of the vehicle. 8. The vehicle identification system according to claim 7 , wherein the information processing device is further configured to divide the X-ray image into a plurality of sub-image blocks, perform feature extraction on the plurality of sub-image blocks, and perform significance weighting on features of each sub-image block to form the internal features of the vehicle. 9. The vehicle identification system according to claim 8 , wherein the vehicle's head has significance larger than that of the vehicle's side. 10. A vehicle identification method comprising: acquiring appearance information of an inspected vehicle and obtaining external features of the vehicle based on the appearance information; acquiring an X-ray image of the vehicle and obtaining internal features of the vehicle from the X-ray image; forming descriptions on the vehicle based on the external features and the internal features; determining a vehicle model of the vehicle from a vehicle model database by utilizing the descriptions; determining a standard X-ray image of the model from a database by utilizing the determined model; and determining whether there is an entrainment in the vehicle by comparing the X-ray image of the inspected vehicle with the standard X-ray image, wherein the appearance information includes contour information obtained by using an infrared sensor, and face information and chassis information of the vehicle obtained using a visible light sensor, and wherein the external features include contour features based on the contour information, face features based on the face information and chassis features based on the chassis information, wherein the contour features, the face features, the chassis features, and internal features are respectively extracted based on characteristics of modalities thereof, and wherein the vehicle is identified by first using the contour features, the face features, the chassis features, and internal features in a sequential form to improve an identification rate of the vehicle model of the vehicle. 11. The method according to claim 10 , further comprising: determining a change region of the X-ray image of the inspected vehicle relative to the standard X-ray image; and presenting the change region to the user. 12. The method according to claim 11 , wherein said determining a change region of the X-ray image of the inspected vehicle relative to the standard X-ray image comprises: performing a registration on the X-ray image of the inspected vehicle and the standard X-ray image; and calculating a difference between the X-ray image of the inspected vehicle and the standard X-ray image. 13. The method according to claim 12 , wherein said presenting the change region to the user comprises: highlighting the change region on the X-ray image.

Assignees

Inventors

Classifications

  • identifying vehicles (G08G1/015, G08G1/054 take precedence) · CPC title

  • with provision for distinguishing between two or more types of vehicles, e.g. between motor-cars and cycles · CPC title

  • Physics · mapped topic

  • Physics · mapped topic

  • Physics · mapped topic

Patent family

Related publications grouped by family.

External sources

Frequently asked questions

Answers are generated from the same data shown on this page.

What does patent US10607483B2 cover?
Disclosed is a vehicle identification method and system. The method includes: acquiring appearance information of an inspected vehicle; obtaining external features of the vehicle based on the appearance information; acquiring a transmission image of the vehicle and obtaining internal features of the vehicle from the transmission image; forming descriptions on the vehicle at least based on the e…
Who is the assignee on this patent?
Nuctech Co Ltd, Univ Tsinghua, Nutech Company Ltd
What technology area does this patent fall under?
Primary CPC classification G08G1/054. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Mar 31 2020 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 4 related publications on this page (citations in our corpus or others sharing the same primary CPC).