Vehicle monitoring system

• US 5,809,161 A
• Filed: 03/22/1993
• Issued: 09/15/1998
• Est. Priority Date: 03/20/1992
• Status: Expired due to Term

• Current Assignee: Commonwealth Scientific & Industrial Research Organisation (Commonwealth Of Australia As Represented By Department Of Industry, Innovation, Climate Change, Science, Research And Tertiary Education)
• Original Assignee: Commonwealth Scientific & Industrial Research Organisation (Commonwealth Of Australia As Represented By Department Of Industry, Innovation, Climate Change, Science, Research And Tertiary Education), Telstra Corporation Limited (Telstra Group Ltd.)
• Inventors: Corke, Peter Ian, Pierce, David Stuart, Simons, Benjamin Francis, Dunn, Paul Alexander, Mills, Dennis Charles, Knight, Rodney Lavis, Jensen, Murray John, Balakumar, Ponnampalam, Auty, Glen William, MacIntyre, Ian Barry
• Primary Examiner(s): Boudreau, Leo
• Assistant Examiner(s): MEHTA, BHAVESH M
• Application Number:
  US08/035,987
• Time in Patent Office: 2,003 Days
• Field of Search: 382/1, 382/48, 382/103-105, 382/107, 348/148, 348/149, 348/143, 348/159, 348/161, 348/169-172, 364/436-438, 340/937-939
• US Class Current: 382/104
• CPC Class Codes: G01P 3/38 using photographic means
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/30261 Obstacle
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/174 involving the use of two or more images
• CPC Class Codes: G06T 7/254 involving subtraction of images
• CPC Class Codes: G06V 10/255 Detecting or recognising potential candidate objects based on visual cues, e.g. shapes
• CPC Class Codes: G06V 20/54 of traffic, e.g. cars on the road, trains or boats
• CPC Class Codes: G06V 20/625 License plates
• CPC Class Codes: G08G 1/017 identifying vehicles G08G1/015, G08G1/054 take precedence
• CPC Class Codes: G08G 1/04 using optical or ultrasonic detectors
• CPC Class Codes: G08G 1/054 photographing overspeeding vehicles

Abstract

An object monitoring system includes a camera node (2) for monitoring movement of an object (18) to determine an acquisition time when an image of the object (18) is to be acquired and acquiring the image at the predetermined time. The system includes a camera (6) which is able to monitor moving objects (18), and image processing circuitry (10), responsive to the camera (6), which is able to detect a predetermined moving object (18) from other moving and static objects. From the image acquired, information identifying the object (18) can be automatically extracted. The system is particularly suited to monitoring and discriminating large vehicles (18) from other vehicles over a multi-lane roadway, and acquiring high resolution images of the large vehicles (18) at a predetermined acquisition point (22). Image data acquired by a plurality of camera nodes (2) can be sent over a digital telecommunications network (45) to a central image processing system (42) which can extract vehicle identifying data, such as licence plate details, and obtain information on vehicle travel between nodes(2).

Claims

1. An object monitoring system comprising

camera means for generating images of an area and for acquiring an image of a predetermined object, and

image processing means including:

means for subtracting a background image of said area from said images of said area to generate difference images representative of moving objects in said area;

segmentation means for processing said difference images to generate region images representative of regions corresponding to parts of said moving objects in said area;

classification means for processing and classifying said region images, said classification means including

means for analyzing the shape of said regions and, on the basis of the analysis, determining valid regions and invalid regions,

clustering means for rejecting said invalid regions and generating, on the basis of the geometry of said valid regions, clusters corresponding to respective ones of said moving objects, and

means for classifying said clusters by comparing at least one characteristic of said clusters to classification data of said system to determine if one of said clusters corresponds to said predetermined object; and

tracking means for tracking said one of said clusters corresponding to said predetermined object to determine an image acquisition time for acquiring said image of said predetermined object.

2. An object monitoring system as claimed in claim 1, wherein said image processing means filters said difference images to disregard pixels within a predetermined intensity range.

3. An object monitoring system as claimed in claim 2, wherein said parts of moving objects correspond to at least a predetermined light level received at said camera means.

4. An object monitoring system as claimed in claim 3, wherein said classification means extends said valid regions to determine if said valid regions have to be combined to form said clusters.

5. An object monitoring system as claimed in claim 4, wherein said classification means includes labeling means for assigning labels to clusters, respectively, for each one of said images of said area to identify said clusters, and for matching clusters over consecutive ones of said images of said area to determine if labels are to be inherited or new labels assigned.

6. An object monitoring system as claimed in claim 5, including means for maintaining a histogram of said at least one characteristic of said clusters, and adjusting said classification data on the basis of said histogram.

7. An object monitoring system as claimed in claim 6, including light intensity means for determining a lighting level of said area, and wherein said predetermined intensity range, said analysis of said regions, extension applied to said valid regions by said classification means, and said classification data are adjusted depending on said lighting level.

8. An object monitoring system as claimed in claim 7, wherein said tracking means includes transformation means for transforming coordinates of said one of said clusters to compensate for a perspective view of said camera means, and means for predicting the speed and position of said one of said clusters for each succeeding image of said images of said area.

9. An object monitoring system as claimed in claim 7, wherein said tracking means determines said acquisition time on the basis of an image capture position and the position of said one of said clusters.

10. An object monitoring system as claimed in claim 9, wherein said camera means includes video camera means for monitoring said moving objects and image capture camera means to acquire said image of said predetermined object at said acquisition time, said image being a high resolution image of said predetermined object.

11. An object monitoring system as claimed in claim 10, wherein said video camera means has a wide field view relative to said image capture camera means, which has a limited field of view.

12. An object monitoring system as claimed in claim 11, including an infrared flash which is synchronized with said image capture camera means, the energy level of said flash being dependent on said lighting level.

13. An object monitoring system as claimed in claim 12, wherein said image capture camera means includes image sensor means and exposure control means for inhibiting saturation of said image sensor means in response to said lighting level.

14. An object monitoring system as claimed in claim 13, wherein said flash includes means for attenuating the emission of visible light therefrom.

15. An object monitoring system as claimed in claim 14, wherein said extension applied by said valid regions is increased when said lighting level corresponds to a night condition.

16. An object monitoring system as claimed in claim 15, wherein said extersion is less for valid regions corresponding to said moving objects distant from said camera means.

17. An object monitoring system as claimed in claim 16, wherein said labeling means performs said matching on the basis of comparing boundaries of said clusters for said consecutive ones of said images of said area.

18. An object monitoring system as claimed in claim 17, wherein said difference images are filtered and used to update said background image.

19. An object monitoring system as claimed in claim 18, including means for triggering said image capture camera means at said acquisition time, comprising means for receiving and storing a number of scan lines corresponding to said acquisition time from said tracking means, means for counting scan lines of said images of said area, and means for generating a trigger signal for said image capture camera means when said count reaches said number.

20. An object monitoring system as claimed in claim 18, wherein said light intensity means generates a histogram of pixel grey levels for said images generated by said video camera means, and determines a day, night or twilight light condition on the basis of the median of said histogram.

21. An object monitoring system as claimed in claim 20, wherein said predetermined intensity range is determined on the basis of the minimum, median and peak of said histogram.

22. An object monitoring system as claimed in claim 21, wherein said analysis includes determining circularity and coverage of said valid and invalid regions.

23. An object monitoring system as claimed in claim 16, wherein said labeling means performs said matching on the basis of comparing centres of said clusters for said consecutive one of said images of said area.

24. An object monitoring system as claimed in claim 7, wherein said camera means includes exposure control means for adjusting camera exposure on the basis of said lighting level.

25. An object monitoring system as claimed in claim 1, including recognition means for processing said image of said predetermined object to obtain information identifying said predetermined object.

26. An object monitoring system as claimed in claim 25, including a plurality of said camera means and image processing means for monitoring a plurality of areas, respectively, and being adapted to communicate with one another so as to transfer information on said predetermined object, said areas being remote with respect to one another.

27. An object monitoring system as claimed in claim 25, including a plurality of said camera means and image processing means for monitoring a plurality of areas, respectively, and being adapted to communicate with a central station so as to transfer information on said predetermined object, said areas being remote with respect to one another.

28. An object monitoring system as claimed in claim 27, wherein said information on said predetermined object is acquired by at least two of said camera means and image processing means and said information can be used to determine the time which said predetermined object took to travel between at least two of said areas.

29. An object monitoring system as claimed in claim 28, wherein said central station includes remote control means for controlling said plurality of said camera means and image processing means from said central station.

30. An object monitoring system as claimed in claim 29, wherein said central station and said plurality of camera means and image processing means include respective telecommunications controllers and communicate using a digital telecommunications network.

31. An object monitoring system as claimed in claim 30, including means for archiving said information and allowing subsequent access thereto.

32. An object monitoring system as claimed in claim 31, wherein said information includes acquired images of said predetermined object and the times of acquisition, and said central station includes said recognition means.

33. An object monitoring system as claimed in claim 32, wherein said recognition means is adapted to process said image of said predetermined object to locate pixels representative of characteristic pixels identifying said object.

34. An object monitoring system as claimed in claim 31, wherein said information includes said identifying information and the times of acquisition of acquired images of said predetermined object, and a plurality of said recognition means are connected to said plurality of camera means and said image processing means, respectively, at the sites of said plurality of camera means and image processing means.

35. An object monitoring system as claimed in claim 28, wherein the objects are vehicles.

36. An object monitoring system as claimed in claim 35, wherein said recognition means comprises means for locating a licence plate in said image of said predetermined object and means for determining the characters of said licence plate, said characters comprising said identifying information.

37. An object monitoring system as claimed in claim 36, wherein said predetermined intensity range covers pixel intensities produced by shadows of said vehicles.

38. An object monitoring system as claimed in claim 37, wherein said invalid regions correspond to headlight reflections produced by said vehicles.

39. An object monitoring system as claimed in claim 38, wherein said predetermined object is a large vehicle, such as a bus or truck.

40. An object monitoring system as claimed in claim 39, wherein said central station includes remote control means for controlling said plurality of camera means and image processing means from said central station.

41. An object monitoring system as claimed in claim 40, wherein said central station and said plurality of camera means and image processing means include respective telecommunications controllers and communicate using a digital telecommunications network.

42. An object monitoring system as claimed in claim 41, including means for archiving said information and allowing subsequent access thereto.

43. An object monitoring system as claimed in claim 42, wherein said information includes said high resolution image and the time of acquisition, and said central station includes said recognition means.

44. An object monitoring system as claimed in claim 42, wherein said information includes said identifying information and the time of acquisition of said high resolution image, and a plurality of said recognition means are connected to said plurality of camera means and image processing means, respectively, at the sites of said plurality of camera means and image processing means.

45. An object monitoring system as claimed in claim 43, wherein said recognition means is adapted to process said high resolution image to locate pixels representative of characteristic pixels identifying said predetermined object.

46. An object monitoring system as claimed in claim 37, wherein said invalid regions correspond to road lane markings within said area.

47. An object monitoring system as claimed in claim 1, wherein said classification means generates and operates on the basis of region feature vectors representative of said regions and cluster feature vectors representative of said clusters.

48. An object monitoring system comprising:

camera means for generating images of an area and for acquiring an image of a predetermined object;

image processing means including;

means for subtracting a background image of said area from said images of said area to generate difference images representative of moving objects in said area,

segmentation means for processing said difference images to generate region images representative of regions corresponding to parts of said moving objects in said area,

classification means for processing said region images, said classification means including

means for analyzing the shape of said regions and, on the basis of the analysis, determining valid regions and invalid regions,

clustering means for rejecting said invalid regions and generating, on the basis of the geometry of said valid regions, clusters corresponding to respective ones of said moving objects, and

means for classifying said clusters by comparing at least one characteristic of said clusters to classification data of said system to determine if one of said clusters corresponds to said predetermined object, and

tracking means for tracking said one of said clusters corresponding to said predetermined object to determine an image acquisition time for acquiring said image of said predetermined object; and

extraction means for processing said image of said predetermined object to extract information identifying said predetermined object.

49. An object monitoring system as claimed in claim 48, including means for transmitting said image of said predetermined object over a digital telecommunications network.

50. An object monitoring system as claimed in claim 48, including a plurality of said camera means and image processing means for monitoring a plurality of areas, respectively, said areas being remote with respect to one another, and means for comparing said information respectively obtained at said areas.

51. An object monitoring system as claimed in claim 48, wherein the objects are vehicles.

52. An object monitoring system as claimed in claim 48, wherein said classification means generates and operates on the basis of region feature vectors representative of said regions and cluster feature vectors representative of said clusters.

53. A vehicle monitoring system comprising:

camera means for generating images of a carriageway and for acquiring images of predetermined vehicles, and image processing means including;

means for subtracting a background image of said carriageway from said images of said carriageway to generate difference images representative of moving vehicles on said carriageway;

segmentation means for processing said difference images to generate region images representative of regions corresponding to parts of said moving vehicles on said carriageway;

classification means for processing said region images, said classification means including

means for analyzing the shape of said regions and, on the basis of the analysis, determining valid regions and invalid regions,

clustering means for rejecting said invalid regions and generating, on the basis of the geometry of said valid regions, clusters corresponding to respective ones of said moving vehicles, and

means for classifying said clusters by comparing at least one characteristic of said clusters to classification data of said system to determine if said clusters correspond to said predetermined vehicles; and

tracking means for tracking said clusters corresponding to said predetermined vehicles to determine image acquisition times for acquiring said images of said predetermined vehicles.

54. A vehicle monitoring system as claimed in claim 53, wherein said camera means includes video camera means for monitoring said carriageway and a plurality of image capture camera means for acquiring said images of said predetermined vehicle for respective lanes of said carriageway.

55. A vehicle monitoring system as claimed in claim 54, wherein said images of said predetermined vehicles are high resolution images covering the width of a lane of said carriageway and enable optical character recognition means to extract licence plate characters of said predetermined vehicles.

56. A vehicle monitoring system as claimed in claim 53, including optical character recognition means for processing said images of said predetermined vehicles to extract licence plate characters identifying said predetermined vehicles.

57. A vehicle monitoring system as claimed in claim 53, wherein said classification means generates and operates on the basis of region feature vectors representative of said regions and cluster feature vectors representative of said clusters.

58. A vehicle monitoring system as claimed in claim 53, wherein said images of said predetermined vehicles are high resolution images covering the width of a lane of said carriageway and enable optical character recognition means to extract licence plate characters of said predetermined vehicles.

59. A vehicle monitoring system comprising:

a plurality of camera means for generating images of respective areas and for acquiring images of predetermined vehicles, said areas being remote with respect to one another; and

a plurality of image processing means including;

means for subtracting background images of said areas from said images of said areas to generate difference images representative of moving vehicles in said areas;

segmentation means for processing said difference images to generate region images representative of regions corresponding to parts of said moving vehicles in said area;

classification means for processing said region images, said classification means including means for analyzing the shape of said regions and, on the basis of the analysis, determining valid regions and invalid regions, clustering means for rejecting said invalid regions and generating, on the basis of the geometry of said valid regions, clusters corresponding to respective ones of said moving vehicles, and means for classifying said clusters by comparing at least one characteristic of said clusters to classification data of said system to determine if said clusters corresponds to said predetermined vehicles;

tracking means for tracking said clusters corresponding to said predetermined vehicles to determine image acquisition times for acquiring said images of said predetermined vehicles; and

recognition means for processing said images of said predetermined vehicles to obtain information identifying said predetermined vehicles.

60. A vehicle monitoring system as claimed in claim 59, including means for comparing said information obtained to determine the average speed between at least two of said areas of at least one of said predetermined vehicles.

61. A vehicle monitoring system as claimed in claim 59, wherein said classification means generates and operates on the basis of region feature vectors representative of said regions and cluster feature vectors representative of said clusters.

62. A vehicle monitoring system comprising:

camera means for generating images of an area and for acquiring an image of a vehicle associated with a law infringement, and image processing means including;

means for subtracting a background image of said area from said images of said area to generate difference images representative of moving vehicles in said area;

segmentation means for processing said difference images to generate region images representative of regions corresponding to parts of said moving vehicles in said area;

classification means for processing said region images, said classification means including

means for analyzing the shape of said regions and, on the basis of the analysis, determining valid regions and invalid regions,

clustering means for rejecting said invalid regions and generating, on the basis of the geometry of said valid regions, clusters corresponding to respective ones of said moving vehicles, and

means for detecting said law infringement by comparing at least one characteristic of said clusters to classification data of said system to determine if one of said clusters corresponds to said vehicle; and

tracking means for tracking said one of said clusters corresponding to said vehicle to determine an image acquisition time for acquiring said image of said vehicle.

63. A vehicle monitoring system as claimed in claim 62, including recognition means for processing said image of said vehicle to obtain information identifying said vehicle.

64. A vehicle monitoring system as claimed in claim 62, wherein said classification means generates and operates on the basis of region feature vectors representative of said regions and cluster feature vectors representative of said clusters.

65. A vehicle monitoring system comprising camera means for generating images of a carriageway and for acquiring high resolution images of large vehicles, such as trucks and buses, and image processing means including:

means for subtracting a background image of said carriageway from said images of said carriageway to generate difference images representative of moving vehicles of said carriageway;

segmentation means for processing said difference images to generate region images representative of regions corresponding to parts of said moving vehicles on said carriageway;

classification means for processing said region images, said classification means including

means for analyzing the shape of said regions and, on the basis of the analysis, determining valid regions and invalid regions,

clustering means for rejecting said invalid regions and generating, on the basis of the geometry of said valid regions, clusters corresponding to respective ones of said moving vehicles, and

means for classifying said clusters by comparing of at least one characteristic of said clusters to classification data of said system to determine if said clusters correspond to said large vehicles; and

tracking means for tracking said clusters corresponding to said large vehicles to determine an image acquisition time for acquiring said high resolution images of said large vehicles.

66. A vehicle monitoring system as claimed in claim 65, including recognition means for automatically extracting information on said large vehicles, such as licence plate characters, from said high resolution images.

67. A vehicle monitoring system as claimed in claim 65, wherein said classification means generates and operates on the basis of region feature vectors representative of said regions and cluster feature vectors representative of said clusters.

68. An object monitoring system comprising:

video camera means for generating images of an area to monitor moving objects in said area;

image capture camera means for acquiring a high resolution image of a predetermined object; and

image processing means including

means for subtracting a background image of said area from said images of said area to generate difference images representative of said moving objects in said area;

segmentation means for processing said difference images to generate region images representative of regions corresponding to parts of said moving objects in said area;

classification means for processing said region images, said classification means including

means for analyzing the shape of said regions and, on the basis of the analysis, determining valid regions and invalid regions,

clustering means for rejecting said invalid regions and generating, on the basis of the geometry of said valid regions, clusters corresponding to respective ones of said moving objects, and

means for classifying said clusters by comparing at least one characteristic of said clusters to classification data of said system to determine if one of said clusters corresponds to said predetermined object; and

tracking means for tracking said one of said clusters corresponding to said predetermined object to determine an image acquisition time for said image capture means to acquire said high resolution image of said predetermined object.

69. The object monitoring system of claim 68 further including a plurality of said video camera means and image processing means for monitoring a plurality of said areas, respectively, said areas being remote with respect to one another, and means for comparing said information respectively obtained at said areas.

70. The object monitoring system of claim 68, wherein the predetermined object is a vehicle and said area is a carriageway.

71. The object monitoring system of claim 70 further including a plurality of image capture camera means for acquiring said image of said vehicle in respective lanes of said carriageway.

72. The object monitoring system of claim 68 further including recognition means for processing said image of said predetermined object to obtain information identifying said object.

73. An object monitoring system comprising:

video camera means for generating images of an area to monitor moving objects in said area;

image capture camera means for acquiring a high resolution image of a predetermined object; and

image processing means including

means for subtracting a background image of said area from said images of said area to generate difference images representative of said moving objects in said area;

segmentation means for processing said difference images to generate region images representative of regions corresponding to parts of said moving objects in said area;

classification means for processing said region images, said classification means including

means for analyzing the shape of said regions and, on the basis of the analysis, determining valid regions and invalid regions,

clustering means for rejecting said invalid regions and generating, on the basis of the geometry of said valid regions, clusters corresponding to respective ones of said moving objects, and

means for classifying said clusters by comparing at least one characteristic of said clusters to classification data of said system to determine if one of said clusters corresponds to said predetermined object;

tracking means for tracking said one of said clusters corresponding to said predetermined object to determine an image acquisition time for said image capture camera means to acquire said high resolution image of said predetermined object; and

extraction means for processing said image of said predetermined object to extract information identifying said predetermined object.

74. The object monitoring system of claim 73, including a plurality of said video camera means and image processing means for monitoring a plurality of areas, respectively, said areas being remote with respect to one another, and means for comparing said information respectively obtained at said areas.

75. The object monitoring system of claim 73, wherein the predetermined object is a vehicle and said area is a carriageway.

76. The object monitoring system of claim 75 further including a plurality of image capture camera means for acquiring said image of said vehicle in respective lanes of said carriageway.

77. The object monitoring system of claim 73 further including recognition means for processing said image of said predetermined object to obtain information identifying said object.

78. A vehicle monitoring system comprising:

video camera means for generating images of a carriageway to monitor moving vehicles in said carriageway;

image capture camera means for acquiring a high resolution image of a predetermined vehicle; and

image processing means including

means for subtracting a background image of said carriageway from said images of said carriageway to generate difference images representative of said moving vehicles on said carriageway;

segmentation means for processing said difference images to generate region images representative of regions corresponding to parts of said moving vehicles on said carriageway;

classification means for processing said region images, said classification means including

means for analyzing the shape of said regions and, on the basis of the analysis, determining valid regions and invalid regions,

clustering means for rejecting said invalid regions and generating, on the basis of the geometry of said valid regions, clusters corresponding to respective ones of said moving vehicles, and

means for classifying said clusters by comparing at least one characteristic of said clusters to classification data of said system to determine if said clusters correspond to said predetermined vehicle; and

tracking means for tracking said clusters corresponding to said predetermined vehicle to determine an image acquisition time for said image capture camera means to acquire said high resolution image of said predetermined vehicle.

79. The vehicle monitoring system of claim 78, including a plurality of said video camera means and image processing means for monitoring a plurality of carriageways, respectively, said carriageways being remote with respect to one another, and means for comparing said information respectively obtained at said carriageways.

80. The vehicle monitoring system of claim 78 further including a plurality of image capture camera means for acquiring said image of said predetermined vehicle in respective lanes of said carriageway.

81. The vehicle monitoring system of claim 78 further including recognition means for processing said image of said predetermined vehicle to obtain information identifying said vehicle.

82. A vehicle monitoring system comprising:

a plurality of video camera means for generating images of respective areas to monitor moving vehicles in said area, said areas being remote with respect to one another;

a plurality of image capture camera means for acquiring a high resolution image of one or more predetermined vehicles; and

a plurality of image processing means including

means for subtracting background images of said areas from said images of said areas to generate difference images representative of said moving vehicles in said areas;

segmentation means for processing said difference images to generate region images representative of regions corresponding to parts of said moving vehicles in said areas;

classification means for processing said region images, said classification means including

means for analyzing the shape of said regions and, on the basis of the analysis, determining valid regions and invalid regions,

clustering means for rejecting said invalid regions and generating, on the basis of the geometry of said valid regions, clusters corresponding to respective ones of said moving vehicles, and

means for classifying said clusters by comparing at least one characteristic of said clusters to classification data of said system to determine if said clusters correspond to said predetermined vehicle;

tracking means for tracking said clusters corresponding to said predetermined vehicle to determine image acquisition times for acquiring said image of said predetermined vehicle; and

recognition means for processing said images of said predetermined vehicle to obtain information identifying said predetermined vehicle.

83. The vehicle monitoring system of claim 82, wherein said area is a carriageway, and said image capture camera means acquire said images of said predetermined vehicle in respective lanes of said carriageway.

84. A vehicle monitoring system comprising:

video camera means for generating images of an area to monitor moving vehicles in said area;

image capture camera means for acquiring a high resolution image of a vehicle associated with a law infringement; and

image processing means including

means for subtracting a background image of said area from said images of said area to generate difference images representative of said moving vehicles in said area;

segmentation means for processing said difference images to generate region images representative of regions corresponding to parts of said moving vehicles in said area;

classification means for processing said region images, said classification means including

means for analyzing the shape of said regions and, on the basis of the analysis, determining valid regions and invalid regions,

clustering means for rejecting said invalid regions and generating, on the basis of the geometry of said valid regions, clusters corresponding to respective ones of said moving vehicles, and

means for detecting said law infringement by comparing at least one characteristic of said clusters to classification data of said system to determine if one of said clusters corresponds to said vehicle; and

tracking means for tracking said one of said clusters corresponding to said vehicle to determine an image acquisition time for said image capture camera means to acquire said high resolution image of said vehicle.

85. The vehicle monitoring system of claim 84, including a plurality of said video camera means and image processing means for monitoring a plurality of areas, respectively, said areas being remote with respect to one another, and means for comparing said information respectively obtained at said areas.

86. The vehicle monitoring system of claim 84 further including a plurality of image capture camera means for acquiring said image of said vehicle in respective lanes of said carriageway.

87. The vehicle monitoring system of claim 84 further including recognition means for processing said image of said vehicle associated with said law infringement to obtain information identifying said vehicle.

88. A vehicle monitoring system comprising:

video camera means for generating images of a carriageway to monitor moving vehicles in said area;

image capture camera means for acquiring a high resolution image of a large vehicle, such as a truck and a bus; and

image processing means including

means for subtracting a background image of said carriageway from said images of said carriageway to generate difference images representative of said moving vehicles on said carriageway;

segmentation means for processing said difference images to generate region images representative of regions corresponding to parts of said moving vehicles on said carriageway;

classification means for processing said region images, said classification means including

means for analyzing the shape of said regions and, on the basis of the analysis, determining valid regions and invalid regions,

clustering means for rejecting said invalid regions and generating, on the basis of the geometry of said valid regions, clusters corresponding to respective ones of said moving vehicles, and

means for classifying said clusters by comparing at least one characteristic of said clusters to classification data of said system to determine if said clusters correspond to said large vehicle; and

tracking means for tracking said clusters corresponding to said large vehicle to determine an image acquisition time for said image capture camera means to acquire said high resolution image of said large vehicle.

89. The vehicle monitoring system of claim 88, including a plurality of said video camera means and image processing means for monitoring a plurality of carriageways, respectively, said carriageways being remote with respect to one another, and means for comparing said information respectively obtained at said carriageways.

90. The vehicle monitoring system of claim 88 further including a plurality of image capture camera means for acquiring said image of said large vehicle in respective lanes of said carriageway.

91. The vehicle monitoring system of claim 88 further including recognition means for processing said image of said large vehicle to obtain information identifying said vehicle.