The present disclosure generally relates to high contrast retroreflective sheeting and license plates, methods of making the high contrast retroreflective sheeting and license plates, and automated license plate reader systems capable of reading the high contrast retroreflective sheeting and license plates.
Automatic Vehicle Recognition (AVR) is a term applied to the detection and recognition of a vehicle by an electronic system. Exemplary uses for AVR include, for example, automatic tolling, traffic law enforcement, searching for vehicles associated with crimes, and facility access control. Ideal AVR systems are universal (i.e., they are able to read all license plates with 100% accuracy). The two main types of AVR systems in use today are (1) systems using RFID technology to read an RFID tag attached to a vehicle and (2) systems using a machine or device to read a machine-readable code attached to a vehicle.
One advantage of RFID systems is their high accuracy, which is achieved by virtue of error detection and correction information contained on the RFID tag. Using well known mathematical techniques (cyclic redundancy check, or CRC, for example), the probability that a read is accurate (or the inverse) can be determined. However, RFID systems have some disadvantages, including that not all vehicles include RFID tags. Also, existing unpowered “passive” RFID tag readers may have difficulty pinpointing the exact location of an object. Rather, they simply report the presence or absence of a tag in their field of sensitivity. Moreover, many RFID tag readers only operate at short range, function poorly in the presence of metal, and are blocked by interference when many tagged objects are present. Some of these problems can be overcome by using active RFID technology or similar methods. However, these techniques require expensive, power-consuming electronics and batteries, and they still may not determine position accurately when attached to dense or metallic objects.
Machine vision systems (often called Automated License Plate Readers or ALPR systems) use a machine or device to read a machine-readable code attached to a vehicle. In many embodiments, the machine readable code is attached to, printed on, or adjacent to a license plate. One exemplary ALPR system is shown schematically in
Prior art methods of creating high contrast license plates for use in ALPR systems involve including materials that absorb in the infra-red wavelength range and transmit in the visible wavelength range. For example, U.S. Pat. No. 6,832,728 describes license plates including visible transmissive, infra-red opaque indicia. U.S. Patent Publication No. 2007/139775 describes license plates including infra-red blocking materials that create contrast on the license plate. U.S. Pat. No. 3,758,193 describes infra-red transmissive, visible absorptive materials for use on retroreflective sheeting.
The present inventors recognized the need for retroreflective sheeting having high contrast in the infra-red wavelength range while maintaining the color characteristics of the retroreflective sheeting in the visible wavelength range. The present inventors also recognized the need for wavelength independent, high contrast retroreflective sheeting. The present inventors also recognized the need for license plates including such sheeting and OCR and/or ALPR systems capable of detecting such license plates.
The present inventors recognized that high contrast, wavelength independent retroreflective sheeting could be made by including a light scattering material on at least a portion of the retroreflective sheeting. The light scattering material reduces the brightness of the retroreflective sheeting without substantially changing the appearance of the retroreflective sheeting when viewed under scattered light.
Some preferred embodiments of the present disclosure relate to retroreflective sheeting, comprising: indicia including a light scattering material. Other preferred embodiments of the present disclosure relate to a license plate comprising the retroreflective sheeting described above. Other preferred embodiments of the present disclosure relate an optical character recognition system, comprising: an optical character recognition camera; a light source emitting infra-red light that is coaxial with the optical character recognition camera; and a license plate including the retroreflective sheeting described above.
The systems, methods, and apparatuses of the present disclosure generally describe the inclusion of a light scattering material on at least a portion of retroreflective sheeting. The light scattering material reduces the brightness of the retroreflective sheeting without substantially changing the appearance of the retroreflective sheeting when viewed under scattered light, thereby creating a high contrast, wavelength independent, retroreflective sheeting. Although existing license plates have included infra-red absorbing, blocking, opaque, and transmissive materials, none of have included light scattering materials to create high contrast. The use of light scattering materials has certain advantages over existing infra-red absorbing, blocking, opaque, and transmissive materials. For example, the contrast of a license plate including light scattering material is wavelength independent in that the indicia formed using light scattering materials has high contrast in retroreflection but a license plate viewed under normal (scattering) lighting conditions will still have whatever aesthetically pleasing look that is desired. This wavelength independence permits greater flexibility in the choice of a camera for use in an OCR or ALPR system that reads license plates including light scattering materials. Further, while it is difficult and expensive to find materials that absorb infra-red light but show color in visible, scattered light, it is relatively easy and inexpensive to find materials that that scatter infra-red light without substantially changing the appearance of the retroreflective sheeting when viewed under scattered light.
The light scattering material is preferably used to create indicia on the retroreflective sheeting or license plate. Exemplary indicia include, for example, the license plate number or identifier. The light scattering material can be a surface-scattering material or can be a bulk-scattering material. Where a bulk-scattering material is used, it can be included in the indicia ink or can be placed under the indicia ink. If the light scattering material is placed under the indicia ink, it is preferably the same color as the substrate (e.g., retroreflective sheeting) so that it does not change the appearance of the indicia in scattered light. Exemplary infra-red light scattering materials include, for example, inks, toners, dyes, and tapes. Where inks, toners, or dyes are used, they are preferably flat (rather than glossy) since glossy inks, toners, and dyes may not adequately scatter the infra-red light. Alternatively, the license plate can simply be selectively roughed by, for example, sanding or bead blasting, in the areas that are meant to be light scattering. In such implementations, the top surface of the license plate acts as the light scattering material.
Some exemplary embodiments of a license plate onto which has been printed a light scattering material are shown in
The contrast of a digital image is the grey value of the appropriately selected light areas in a ratio to the grey value of the appropriately selected dark areas. The contrast of an object is theoretically the same as the contrast of an image of that object. However the lighting conditions need to be specified and the exposure needs to be carefully controlled. The light areas must not saturate the detector and the dark areas must be sufficiently above the noise level that the noise does not substantially affect the measurement. For these reasons, it is difficult (sometimes impossible) to measure the contrast of high contrast objects from a single image. An 8 bit camera can theoretically measure a contrast of up to 256:1. However, if the noise level is about 10 counts, one would prefer to use a minimum measurement of about 30 counts. In order to avoid saturation of the image, one would prefer to use a maximum of about 200 counts. This limits the maximum contrast from a single image to 200/30 or about 6.7:1. In order to overcome these problems, one can use several images at different, carefully controlled lighting and exposure settings to extend the dynamic rage of the measurement.
Some preferred embodiments of the present disclosure also describe OCR and/or ALPR systems capable of detecting the retroreflective sheeting and license plates described above. One exemplary OCR or ALPR system could include an OCR camera (e.g., Model 832, Spike™ sold by PIPS Technology, a division of Federal Signal Company); an infra-red light source; and a license plate as described above. The light source preferably emits light that is nearly coaxial with the viewer of the OCR camera.
The recitation of all numerical ranges by endpoint is meant to include all numbers subsumed within the range (i.e., the range 1 to 10 includes, for example, 1, 1.5, 3.33, and 10).
Those having skill in the art will appreciate that many changes may be made to the details of the above-described embodiments and implementations without departing from the underlying principles thereof. Further, various modifications and alterations of the present invention will become apparent to those skilled in the art without departing from the spirit and scope of the invention. The scope of the present application should, therefore, be determined only by the following claims.
This application is a national stage filing under 35 U.S.C. 371 of PCT/US2010/051507, filed Oct. 5, 2010, which claims priority to Provisional Application No. 61/249,765, filed Oct. 8, 2009, the disclosure of which is incorporated by reference in its/their entirety herein.
Filing Document | Filing Date | Country | Kind | 371c Date |
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PCT/US2010/051507 | 10/5/2010 | WO | 00 | 4/5/2012 |
Publishing Document | Publishing Date | Country | Kind |
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WO2011/044149 | 4/14/2011 | WO | A |
Number | Name | Date | Kind |
---|---|---|---|
3758193 | Tung | Sep 1973 | A |
3917232 | Lindner | Nov 1975 | A |
4268179 | Long | May 1981 | A |
4368979 | Ruell | Jan 1983 | A |
4491923 | Look | Jan 1985 | A |
4605946 | Robinson, Jr. | Aug 1986 | A |
4792258 | Goff | Dec 1988 | A |
5029023 | Bearden | Jul 1991 | A |
5585616 | Roxby | Dec 1996 | A |
5656360 | Faykish | Aug 1997 | A |
5672381 | Rajan | Sep 1997 | A |
5760384 | Itoh | Jun 1998 | A |
5915032 | Look | Jun 1999 | A |
6024455 | O'Neill | Feb 2000 | A |
6120636 | Nilsen | Sep 2000 | A |
6448889 | Hudson | Sep 2002 | B1 |
6650765 | Alves | Nov 2003 | B1 |
6832728 | Kennedy | Dec 2004 | B2 |
7198426 | Kang | Apr 2007 | B2 |
7258505 | Dehart | Aug 2007 | B2 |
7329447 | Chirhart | Feb 2008 | B2 |
7350328 | Garcia | Apr 2008 | B1 |
7351008 | Yodock, III | Apr 2008 | B2 |
7387393 | Reich | Jun 2008 | B2 |
20020044069 | Jenkinson | Apr 2002 | A1 |
20020178627 | Tietze et al. | Dec 2002 | A1 |
20030133594 | Sefton | Jul 2003 | A1 |
20050161505 | Yin | Jul 2005 | A1 |
20050173524 | Schrader | Aug 2005 | A1 |
20070069921 | Sefton | Mar 2007 | A1 |
20070139775 | Reich | Jun 2007 | A1 |
20080001046 | Mettler | Jan 2008 | A1 |
20090097034 | Grygier et al. | Apr 2009 | A1 |
20090267895 | Bunch | Oct 2009 | A1 |
20100151213 | Smithson et al. | Jun 2010 | A1 |
20110084126 | Fleming | Apr 2011 | A1 |
20120281285 | Orensteen et al. | Nov 2012 | A1 |
Number | Date | Country |
---|---|---|
0416742 | Mar 1991 | EP |
WO 2008-007076 | Jan 2008 | WO |
WO 2009-118534 | Oct 2009 | WO |
Number | Date | Country | |
---|---|---|---|
20120195470 A1 | Aug 2012 | US |
Number | Date | Country | |
---|---|---|---|
61249765 | Oct 2009 | US |