AUTOMATIC CLASSIFICATION SYSTEM FOR MOTOR VEHICLES

• US 20150269444A1
• Filed: 03/24/2015
• Published: 09/24/2015
• Est. Priority Date: 03/24/2014
• Status: Abandoned Application

• Current Assignee: Survision
• Original Assignee: Survision
• Inventors: Lameyre, Bruno, Jouannais, Jacques
• Application Number:
  US14/667,577
• Publication Number:
  US 20150269444A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06V 20/54 of traffic, e.g. cars on the road, trains or boats
• CPC Class Codes: G06V 20/63 Scene text, e.g. street names
• CPC Class Codes: G08G 1/015 with provision for distinguishing between two or more types of vehicles, e.g. between motor-cars and cycles
• CPC Class Codes: G08G 1/017 identifying vehicles G08G1/015, G08G1/054 take precedence

Abstract

This automatic classification system according to the invention comprises a data processing unit (20) programmed to classify a vehicle present in the images captured by a camera (6), by processing the captured images, the captured images being intensity matrix images and the camera (6) being positioned capture images of the vehicle in birds-eye view and in three-quarters view, preferably three-quarters front view.

Claims

1. An automatic classification system for motor vehicles traveling on a road, comprising a data processing unit programmed to classify a vehicle present in the images captured by a camera, by processing the captured images, the captured images being intensity matrix images and the camera being positioned capture images of the vehicle in birds-eye view and in three-quarters view.

2. The classification system according to claim 1, wherein the data processing unit is programmed to compute a corrected image from the captured image, so as to reestablish, in the corrected image, the parallelism between parallel elements of the actual scene and the perpendicularity between perpendicular elements of the actual scene.

3. The classification system according to claim 2, wherein computing the corrected image produced therefrom by applying a predetermined transformation matrix to the captured image.

4. The classification system according to claim 1, wherein the data processing unit is programmed to compute a reconstituted image in which a vehicle is visible over its entire length, from a sequence of images in which at least one segment of the vehicle appears.

5. The classification system according to claim 1, wherein the data processing unit is programmed to identify characteristic points of the vehicle appearing in several images of the sequence of images, and to combine the images from the sequence of images based on the identified characteristic points to form the reconstituted image.

6. The classification system according to claim 1, wherein the data processing unit is programmed to compute the length and/or height of the vehicle from the reconstituted image.

7. The classification system according to claim 1, wherein the data processing unit is programmed to compute the number of axles of the vehicle by counting the number of wheels appearing on a side face of the vehicle visible from the reconstituted image.

8. The classification system according to claim 7, wherein the data processing unit is programmed to detect a wheel using an ellipse identification algorithm.

9. The classification system according to claim 8, wherein the data processing unit is programmed to count the number of axles based on the number of predetermined axle configurations.

10. The classification system according to claim 1, wherein the data processing unit is programmed to detect the entry of a new vehicle in the field of the camera by detecting a license plate in the captured images.

11. The classification system according to claim 1, wherein the data processing unit is programmed to detect the separation between a vehicle and the following vehicle based on the road and/or the road marking.

12. The classification system according to claim 1, wherein the data processing unit is programmed to detect the separation between a vehicle and the following vehicle based on photometric characteristics of the road and/or the road marking.

13. The classification system according to claim 1, wherein the data processing unit is programmed to implement learning, of the photometric characteristics of the road and/or the road marking.

16. The automatic classification system according to claim 1, wherein the camera is positioned to capture images of the vehicle in three-quarters front view.

17. The classification system according to claim 13, wherein the data processing unit is programmed to implement learning continuous of the photometric characteristics of the road and/or the road marking.

14. An automatic classification method for motor vehicles traveling on a road, comprising the classification of the vehicle present in the images captured by a camera, by processing images captured by a data processing unit, the captured images being intensity matrix images and the camera being positioned to capture images of the vehicle in birds-eye view and in three-quarters view.

15. A computer program product programmed to implement the method according to claim 14, when it is executed by a data processing unit.

18. The automatic classification method for motor vehicles traveling on a road according to claim 14, wherein the camera is positioned to capture images of the vehicle in birds-eye view and in three-quarters front view.