VEHICLE TRACKING SYSTEM AND TRACKING METHOD THEREOF

• US 20110255740A1
• Filed: 10/15/2010
• Published: 10/20/2011
• Est. Priority Date: 04/15/2010
• Status: Active Grant

• Current Assignee: National Chiao Tung University (Government of The Republic of China)
• Original Assignee: National Chiao Tung University (Government of The Republic of China)
• Inventors: Chen, Yen-Lin, Wu, Bing-Fei, Fan, Chung-Jui, Huang, Hao-Yu
• Granted Patent: US 8,503,725 B2
• Time in Patent Office: Days
• US Class Current: 382/103
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/30236 Traffic on road, railway or crossing
• CPC Class Codes: G06T 7/136 involving thresholding
• CPC Class Codes: G06T 7/187 involving region growing; involving region merging; involving connected component labelling
• CPC Class Codes: G06T 7/246 using feature-based methods, e.g. the tracking of corners or segments
• CPC Class Codes: G06V 20/54 of traffic, e.g. cars on the road, trains or boats
• CPC Class Codes: G06V 2201/08 Detecting or categorising vehicles

Abstract

The present invention discloses a vehicle tracking system and method, and the tracking method comprises the steps of capturing a bright object from an image by the bright object segmentation; labeling the bright object by a connected component labeling method and forming a connected component object; identifying, analyzing and combining the characteristics of the connected component object to form a lamp object by the bright object recognition; tracking the trajectory of the lamp object by a multi-vehicle tracking method; and identifying the type of a vehicle having the lamp object by the vehicle detection/recognition and counting the number of various vehicles.

Claims

1. A vehicle tracking method, comprising the steps of:

capturing a plurality of bright objects from an image by the bright object segmentation;

labeling coordinates of the plurality of bright objects by a connected component object labeling method to form a plurality of connected component objects;

identifying, analyzing and combining characteristics of the plurality of connected component objects by the bright object recognition to form a plurality of lamp objects; and

identifying the type of a vehicle having the plurality of lamp objects by the vehicle detection/recognition, and counting the number of various vehicles.

2. The vehicle tracking method of claim 1, wherein the image is a grey-scale image, and the bright object segmentation determines a plurality of threshold values by a grey scale statistical chart of the grey-scale image, and segments the image to form the plurality of bright objects after objects with same nature and similar characteristics in the grey-scale image are determined according to the plurality of threshold values.

3. The vehicle tracking method of claim 1, wherein the image includes a plurality of lanes that defines a detection area, and the connected component object labeling method includes a coarse scan and a fine scan, for labeling the plurality of adjacent bright objects as the same object by a connected component labeling method to form the plurality of connected component objects.

4. The vehicle tracking method of claim 1, wherein the bright object recognition respectively compares values of the aspect ratio, area and density of the plurality of connected component objects with a maximum aspect ratio threshold value, a minimum aspect ratio threshold value, a maximum area threshold value, a minimum area threshold value and a density critical threshold value to determine the characteristics of the plurality of connected component objects to capture the plurality of lamp objects;

and if the bright object recognition determines that any two of the connected component objects have a horizontal distance and a vertical distance smaller than a horizontal distance threshold value and a vertical distance threshold value respectively, then the paired connected component objects are combined to form a lamp object.

5. The vehicle tracking method of claim 1, wherein the multi-vehicle tracking method tracks the projectory of the plurality of lamp objects;

and if the values of area, width and horizontal distance of any paired lamp objects match a lamp area threshold value, a lamp width threshold value and a lamp horizontal distance threshold value respectively, the multi-vehicle tracking method combines the paired lamp object into one of the lamp objects, and tracks the projectory of the lamp object.

6. The vehicle tracking method of claim 1, wherein the vehicle detection/recognition compares the aspect ratio of the plurality of lamp objects with an aspect ratio threshold value of a motorcycle and an aspect ratio threshold value of an automobile, and determines the type of a vehicle having the plurality of lamp objects according a comparison result.

7. A vehicle tracking system, comprising:

an image capture module, for capturing an image;

a display module, for displaying the image; and

a processing module, comprising;

a bright object segmentation unit, for capturing a plurality of bright objects from an image;

a connected component, for labeling coordinates of the plurality of bright objects by object labeling unit to form a plurality of connected component objects;

a bright object identifying unit, for identifying, analyzing and combining characteristics of the plurality of connected component objects;

a multi-vehicle tracking unit, for tracking a trajectory of the plurality of lamp objects; and

a vehicle identifying unit, for identifying the type of a vehicle having the plurality of lamp objects;

the processing module further counting the number of various vehicles to control the number of various vehicles displayed by the display module.

8. The vehicle tracking system of claim 7, wherein the image is a grey-scale image, and the bright object segmentation unit determines a plurality of threshold values by a grey scale statistical chart of the grey-scale image, and segments the image to form the plurality of bright objects after objects of the same nature and similar characteristics in the grey-scale image are determined according to the plurality of threshold values.

9. The vehicle tracking system of claim 7, wherein the image includes a plurality of lanes that defines a detection area, and the connected component object labeling method includes a coarse scan and a fine scan for labeling the plurality of adjacent bright objects as the same object by a connected component labeling method to form the plurality of connected component objects.

10. The vehicle tracking system of claim 7, wherein the bright object identifying unit respectively compares the values of aspect ratio, area and density of the plurality of connected component objects with a maximum aspect ratio threshold value, a minimum aspect ratio threshold value, a maximum area threshold value, a minimum area threshold value and a density critical threshold value to determine the characteristics of the plurality of connected component objects to capture the plurality of lamp objects;

and if the bright object recognition determines that any two of the connected component objects have a horizontal distance and a vertical distance smaller than a horizontal distance threshold value and a vertical distance threshold value respectively, then the paired connected component objects are combined to form a lamp object.

11. The vehicle tracking system of claim 7, wherein the multi-vehicle tracking unit tracks the projectory of the plurality of lamp objects;

and if the values of area, width and horizontal distance of any paired lamp objects match a lamp area threshold value, a lamp width threshold value and a lamp horizontal distance threshold value respectively, the multi-vehicle tracking method combines the paired lamp objects into one of the lamp objects, and tracks the projectory of the lamp object.

12. The vehicle tracking system of claim 7, wherein the vehicle identifying unit compares the aspect ratio of the plurality of lamp objects with an aspect ratio threshold value of a motorcycle and an aspect ratio threshold value of an automobile, and determines the type of a vehicle having the plurality of lamp objects according a comparison result.