Image processing techniques for a video based traffic monitoring system and methods therefor
First Claim
1. A method of detecting a vehicle within a chevron area in a traffic monitoring system, the method comprising the steps of:
- applying a gray level co-occurrence matrix for the extraction of texture features of a region of interest;
calculating two texture measurements using the gray level co-occurrence matrix, the two texture measurements comprising an angular second moment and a contrast;
comparing the angular second moment ASM and the contrast CON, with a background angular second moment ASMB and a background contrast CONB, the background angular second moment and background contrast measured when no vehicle is present,); and
determining if (|ASMB−
ASM|>
ASMTH-AND|CONB−
CON|<
+(CONTh),wherein if (|ASMB−
ASM|>
ASMTH-AND |CONB−
CON|<
+(CONTh), then a vehicle is not present.
0 Assignments
0 Petitions
Accused Products
Abstract
The present disclosure relates to a number of inventions directed, generally, to the application of image processing techniques to traffic data acquisition using video images. The inventions reside in a traffic monitoring system, the basic function of which is for traffic data acquisition and incident detection. More specifically, the application of image processing techniques for the detection of vehicle, from sequence of video images, as well as the acquisition of traffic data and detection of traffic incident. In one aspect, the present invention provides a method of processing images received from a video based traffic monitoring system. In another aspect, the present invention is directed to a Region Of Interest (ROI) for detection of a moving vehicle and a further aspect is directed to a method of detecting day or night status in a traffic monitoring system. It'"'"'s The application of various algorithms to a video based traffic monitoring system is also considered inventive. Other inventive aspects of the present traffic monitoring system are outlined in the claims.
-
Citations
10 Claims
-
1. A method of detecting a vehicle within a chevron area in a traffic monitoring system, the method comprising the steps of:
-
applying a gray level co-occurrence matrix for the extraction of texture features of a region of interest; calculating two texture measurements using the gray level co-occurrence matrix, the two texture measurements comprising an angular second moment and a contrast; comparing the angular second moment ASM and the contrast CON, with a background angular second moment ASMB and a background contrast CONB, the background angular second moment and background contrast measured when no vehicle is present,); and determining if (|ASMB−
ASM|>
ASMTH-AND|CONB−
CON|<
+(CONTh),wherein if (|ASMB−
ASM|>
ASMTH-AND |CONB−
CON|<
+(CONTh), then a vehicle is not present.- View Dependent Claims (2)
-
-
3. A method of calculating vehicle speed in a traffic monitoring system, the method comprising the steps of:
-
using convolution between two edge-profiles for the extraction of the vehicle speed; and obtaining edge values E(x,y) for all pixels (x,y), within a profile speed zone according to;
and wherein SH and SV are 3×
3 matrices for the extraction of the horizontal vertical edge, respectively.
-
-
4. A method of calculating vehicle speed in a traffic monitoring system, the method comprising the steps of:
-
using convolution between two edge-profiles for the extraction of the vehicle speed; and generating an edge-profile in accordance with
wherein EAVE(y) is the average edge-density of each row of pixels.- View Dependent Claims (5, 6, 7, 8, 9)
-
-
10. A method as claimed in claim in 9, wherein a positive polarity indicates that the vehicle is travelling in a direction of traffic flow, and wherein a negative polarity indicates that the vehicle is travelling in a direction opposite to the direction of traffic flow.
Specification