WO2019084385A1 - Lecteur de code de pneu - Google Patents

Lecteur de code de pneu

Info

Publication number
WO2019084385A1
WO2019084385A1 PCT/US2018/057684 US2018057684W WO2019084385A1 WO 2019084385 A1 WO2019084385 A1 WO 2019084385A1 US 2018057684 W US2018057684 W US 2018057684W WO 2019084385 A1 WO2019084385 A1 WO 2019084385A1
Authority
WO
WIPO (PCT)
Prior art keywords
images
plural
camera unit
lights
cameras
Prior art date
Application number
PCT/US2018/057684
Other languages
English (en)
Inventor
Roger Tracy
Cesare Santanera
David Boyle
Jeffrey HISLOP
Original Assignee
Tire Profiles, Llc
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Tire Profiles, Llc filed Critical Tire Profiles, Llc
Publication of WO2019084385A1 publication Critical patent/WO2019084385A1/fr

Links

Classifications

    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29D—PRODUCING PARTICULAR ARTICLES FROM PLASTICS OR FROM SUBSTANCES IN A PLASTIC STATE
    • B29D30/00—Producing pneumatic or solid tyres or parts thereof
    • B29D30/0016—Handling tyres or parts thereof, e.g. supplying, storing, conveying
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/10—Image acquisition
    • G06V10/12—Details of acquisition arrangements; Constructional details thereof
    • G06V10/14—Optical characteristics of the device performing the acquisition or on the illumination arrangements
    • G06V10/147—Details of sensors, e.g. sensor lenses
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V10/00—Arrangements for image or video recognition or understanding
    • G06V10/70—Arrangements for image or video recognition or understanding using pattern recognition or machine learning
    • G06V10/82—Arrangements for image or video recognition or understanding using pattern recognition or machine learning using neural networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
    • G06V30/10—Character recognition
    • G06V30/14—Image acquisition
    • G06V30/1431—Illumination control
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B29—WORKING OF PLASTICS; WORKING OF SUBSTANCES IN A PLASTIC STATE IN GENERAL
    • B29D—PRODUCING PARTICULAR ARTICLES FROM PLASTICS OR FROM SUBSTANCES IN A PLASTIC STATE
    • B29D30/00—Producing pneumatic or solid tyres or parts thereof
    • B29D30/0016—Handling tyres or parts thereof, e.g. supplying, storing, conveying
    • B29D2030/0027—Handling cured tyres, e.g. transferring or storing after vulcanizing
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
    • G06V30/00—Character recognition; Recognising digital ink; Document-oriented image-based pattern recognition
    • G06V30/10—Character recognition

Definitions

  • the present disclosure relates generally to devices for recognizing
  • alphanumeric characters and, in particular, alphanumeric characters on the sidewalls of tires are examples of alphanumeric characters and, in particular, alphanumeric characters on the sidewalls of tires.
  • Tire Identification codes are embossed or molded into the sidewalls of tires sold in the United States. Other types of tire markings may be used in other countries and tires destined for use in the US may be manufactured with DOT tire codes. These codes identify information relevant to the tire with alphanumeric characters arranged in three sets of four characters. The characters, being black on a black surface, are difficult to read under normal lighting, and even more difficult to read in dim lighting, such as in a garage.
  • a device that could reliably read a DOT tire code electronically would be advantageous.
  • reading in this sense means that the individual alphanumeric characters in the sequence they appear on the tire sidewall are detected and replicated electronically.
  • reading in this sense means that the individual alphanumeric characters in the sequence they appear on the tire sidewall are detected and replicated electronically.
  • the letter “A” and the number “9” embossed or molded into the sidewall of a particular tire would be detected in images of the tire sidewall by a programmed computer and
  • the system includes a camera unit having one or two cameras in a palm-sized housing.
  • the camera unit captures a series of images using plural lights that sequentially illuminate the tire code from different angles.
  • the sequence of images is made using only artificial light emanating from within the camera and is a fixed, particular sequence.
  • the sequence of images captured by the camera unit are forwarded wirelessly to a server for storage and to a processor for detection and reading of the alphanumeric DOT code of the particular tire.
  • the DOT tire code is displayed for the user.
  • a feature of the disclosure is the use of at least two lighting elements, to be used in sequence to light the tire code.
  • Each lighting element used is directed at the tire code from a different angle in order to highlight different features of the topography of the code to improve tire code detection and reading accuracy.
  • a feature of the disclosure is that banks of light-emitting diodes (LEDs) may be used for their small size, brightness, low energy consumption and their convenience for directing the light where desired. Moreover, the imaging devices are closer to the tire code when the images are acquired.
  • LEDs light-emitting diodes
  • the camera unit contains one or two solid-state cameras (e.g., a charge-coupled device (CCD) or complementary metal-oxide-semiconductor (CMOS) in side-by-side relationship with fields of view that overlap to capture the DOT tire code in a small housing, which can acquire the requisite set of images whether held right side up or upside down.
  • the cameras may have one mega-pixels each for images having good resolution, but the method may need higher resolution to read very small characters.
  • each camera has its own lens and the housing has a window protecting both cameras.
  • a feature of the disclosure is that the camera unit uses a server and
  • a neural network may be used to extract the DOT codes with greater speed and accuracy.
  • a convolutional neural network which is a special kind of multi-layer neural network, may be used.
  • computers are programmed to self-train based on a back-propagation algorithm.
  • Convolutional neural networks such as LeNet-5, are designed to recognize visual patterns directly from pixel images with minimal programming. Such neural networks can learn to recognize patterns such as hand-written characters with extreme variability, and are robust against distortions and simple geometric
  • FIG. 1 is a side view of the present camera unit, according to an aspect of the disclosure.
  • FIG. 2 is a front view of the present unit, according to an aspect of the disclosure.
  • FIG. 3 is an alternative view of the front view of the camera unit, according to an aspect of the disclosure.
  • FIG. 4 is a schematic diagram of the present system in use, according to an aspect of the disclosure.
  • the system includes a camera unit 10 operable to capture a set of images of the sidewall of a tire at the location of the US DOT tire code.
  • the set of images makes it possible to discern and read the tire code by a processor and then display it for a user to read.
  • the term "camera unit” will be used herein to refer to a device that has a camera-like function but captures a set of images rather than just one at a time, and which set of images facilitates discernment of the information contained in the images.
  • the term camera unit 10 will be further defined and characterized below.
  • images are taken with lighting directed at the tire from different angles within the camera to highlight topographic features of the tire sidewall, such as edges and flat surfaces, in the vicinity of the embossed or molded tire code.
  • the processor may be physically separated from the camera unit 10 to reduce the size of the camera unit 10 and to provide the requisite computing power for reading the tire code.
  • the processor is part of a server remote from the camera unit 10 but accessible via Wi-Fi or other wireless type of communication channel. Wi-fi is a facility that allows computers, smartphones, or other devices to connect to the Internet or to communicate with one another wirelessly within a particular area.
  • the camera unit 10 is a small, hand-held housing 14 that contains two side-by-side imaging devices 18, 22. Each imaging device 18, 22, has a field of view. The fields of view of these imaging devices 18, 22 overlap so that images captured by them can be presented as one image. Two (or more) imaging devices 18, 22, in a rectangular array enable the capturing of a combined, close- up image of the tire code.
  • a tire code contains 12 (and sometimes fewer) alphanumeric characters in a sequence that fits within a thin, horizontal rectangle.
  • Two smaller imaging devices 18, 22, in side-by-side relationship may capture a rectangular image more efficiently than a larger, square one.
  • the camera unit 10 has a single transparent covering, such as glass or acrylic, over its front opening or window.
  • Imaging devices 18, 22, may have a single camera 34 with a lens 36 and an imager 38, as seen in FIGS. 1 and 2, or two cameras 18, 22, as shown in FIG. 3, which has a first lens 26 and a second lens 30, respectively, each of which has an imager 20 and 24, respectively.
  • the camera unit 10 may have an on-off button, perhaps a camera control button for the operator to verify that the image of the DOT code is visible and in focus, and an imaging sequence start button.
  • Also inside camera unit 10 are plural banks of lights, which may comprise a row of light-emitting diodes (LEDs).
  • Banks of LEDs 38, 42, 46, and 50 may arranged on each of the four sides of the housing 14 of camera unit 10 near window and oriented so as to direct lighting through the glass to the exterior of camera unit 10 at different angles. Combinations of one or more of these banks of LEDs proceed in a pre-determined sequence to illuminate the tire code.
  • the camera covering is brought close to the tire code so that the camera walls enclose the tire code and help to exclude ambient light when the banks of lights begin to flash in sequence.
  • a sequence may be a single bank of lights from each of the four sides for four images and then two or four more images with different combinations of light banks at adjacent corners lighted.
  • Reading images can be done with any of several techniques such as standard optical character recognition software or proprietary software including neural network techniques.
  • Convolutional neural networks are multi-layer neural networks. Like many other neural networks, they are programmed with a version of a back- propagation algorithm. Where they differ from other neural networks is in the architecture of the software.
  • Convolutional neural networks are designed to recognize visual patterns directly from pixel images with minimal preprocessing. They can recognize patterns with extreme variability (such as handwritten characters) and are robust to distortions and simple geometric transformations.
  • LeNet-5 is an example of a convolutional network designed for handwritten and machine-printed character recognition.
  • the set of images of the tire code of a tire 54 made by the camera unit 10 and received by a handheld or mobile device 58 are transmitted, e.g., via Wi-Fi, to a cloud-base server 60 (or other server) for reading the code.
  • the code once read, is displayed on the handheld or mobile device 58 as a printed code, and may be displayed by the handheld or mobile device along 58 with the image captured by the camera unit 10.
  • the file may be stored or entered into a database depending on use. It may be transmitted to the hand held or mobile device 58, which may be a tablet or other small computer, for the intended use of the file, whether that be inventory control at a manufacturing warehouse or to check tire recall information at a repair shop.
  • the hand held or mobile device 58 which may be a tablet or other small computer, for the intended use of the file, whether that be inventory control at a manufacturing warehouse or to check tire recall information at a repair shop.

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Multimedia (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Health & Medical Sciences (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Evolutionary Computation (AREA)
  • General Health & Medical Sciences (AREA)
  • Mechanical Engineering (AREA)
  • Artificial Intelligence (AREA)
  • Computing Systems (AREA)
  • Databases & Information Systems (AREA)
  • Medical Informatics (AREA)
  • Software Systems (AREA)
  • Vascular Medicine (AREA)
  • Character Discrimination (AREA)

Abstract

La présente invention concerne un système et un procédé de lecture de codes de pneus DOT. Le système comprend une unité de caméra dans un boîtier de la taille de la paume de la main. Le boîtier contient une paire de dispositifs d'imagerie adjacents et plusieurs rangées d'éclairage à DEL déployées autour de la fenêtre de l'unité de caméra de façon à éclairer le code de pneu sous différents angles. La fenêtre de l'unité de caméra est orientée vers la paroi latérale du pneu et sur le code du pneu de façon à obscurcir la lumière externe et à obtenir une vue rapprochée du code du pneu. Les rangées de lumières éclairent alors le code du pneu selon une séquence prédéterminée pour permettre aux dispositifs d'imagerie de capturer une série d'images de l'utilisation d'un réseau neuronal à utiliser pour une reconnaissance de caractères et un affichage du code du pneu.
PCT/US2018/057684 2017-10-26 2018-10-26 Lecteur de code de pneu WO2019084385A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
US201762577591P 2017-10-26 2017-10-26
US62/577,591 2017-10-26

Publications (1)

Publication Number Publication Date
WO2019084385A1 true WO2019084385A1 (fr) 2019-05-02

Family

ID=66246737

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2018/057684 WO2019084385A1 (fr) 2017-10-26 2018-10-26 Lecteur de code de pneu

Country Status (1)

Country Link
WO (1) WO2019084385A1 (fr)

Cited By (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB2580675A (en) * 2019-01-23 2020-07-29 Wheelright Ltd Tyre sidewall imaging method
WO2020229132A1 (fr) * 2019-05-14 2020-11-19 Wheelright Limited Procédé d'imagerie de flanc de pneu
WO2021150922A1 (fr) * 2020-01-24 2021-07-29 Barram Peter J Scanners de pneu portables et procédés et systèmes associés
DE102021203559A1 (de) 2021-04-12 2022-10-13 Continental Reifen Deutschland Gmbh Verfahren zur Erkennung einer Identifikationsnummer

Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4700078A (en) * 1986-02-07 1987-10-13 Bridgestone Corporation Method and apparatus for detecting tire information mark
US20030084977A1 (en) * 2000-11-20 2003-05-08 Tullio Gonzaga Apparatus for the identification and maintenance of tyres and wheels with tyres
US20120169856A1 (en) * 2010-12-30 2012-07-05 Evan Ahmed System and method for tire registration
WO2014117870A1 (fr) * 2013-02-04 2014-08-07 Me-Inspection Sk Procédé, agencement de mesure et système servant à inspecter un objet tridimensionnel
US20160029006A1 (en) * 2013-07-25 2016-01-28 Jack Marshall Zoken System and Method for Analysis of Surface Features
US20160127625A1 (en) * 2013-04-23 2016-05-05 Robert Bosch Gmbh device and method for recognizing inscriptions on vehicle tires
WO2017074759A1 (fr) * 2015-10-29 2017-05-04 Roger Tracy Système et procédé de lecture d'un code de pneu et d'obtention d'informations liées à un pneu
WO2017103814A1 (fr) * 2015-12-16 2017-06-22 Pirelli Tyre S.P.A. Dispositif et procédé pour l'analyse de pneus

Patent Citations (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US4700078A (en) * 1986-02-07 1987-10-13 Bridgestone Corporation Method and apparatus for detecting tire information mark
US20030084977A1 (en) * 2000-11-20 2003-05-08 Tullio Gonzaga Apparatus for the identification and maintenance of tyres and wheels with tyres
US20120169856A1 (en) * 2010-12-30 2012-07-05 Evan Ahmed System and method for tire registration
WO2014117870A1 (fr) * 2013-02-04 2014-08-07 Me-Inspection Sk Procédé, agencement de mesure et système servant à inspecter un objet tridimensionnel
US20160127625A1 (en) * 2013-04-23 2016-05-05 Robert Bosch Gmbh device and method for recognizing inscriptions on vehicle tires
US20160029006A1 (en) * 2013-07-25 2016-01-28 Jack Marshall Zoken System and Method for Analysis of Surface Features
WO2017074759A1 (fr) * 2015-10-29 2017-05-04 Roger Tracy Système et procédé de lecture d'un code de pneu et d'obtention d'informations liées à un pneu
WO2017103814A1 (fr) * 2015-12-16 2017-06-22 Pirelli Tyre S.P.A. Dispositif et procédé pour l'analyse de pneus

Cited By (6)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
GB2580675A (en) * 2019-01-23 2020-07-29 Wheelright Ltd Tyre sidewall imaging method
US11922683B2 (en) 2019-01-23 2024-03-05 Wheelright Limited Tyre sidewall imaging method
WO2020229132A1 (fr) * 2019-05-14 2020-11-19 Wheelright Limited Procédé d'imagerie de flanc de pneu
US11669952B2 (en) 2019-05-14 2023-06-06 Wheelright Limited Tyre sidewall imaging method
WO2021150922A1 (fr) * 2020-01-24 2021-07-29 Barram Peter J Scanners de pneu portables et procédés et systèmes associés
DE102021203559A1 (de) 2021-04-12 2022-10-13 Continental Reifen Deutschland Gmbh Verfahren zur Erkennung einer Identifikationsnummer

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