WO2021079006A1 - Procédé de gestion des données d'image et dispositif d'éclairage automobile - Google Patents

Procédé de gestion des données d'image et dispositif d'éclairage automobile Download PDF

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Publication number
WO2021079006A1
WO2021079006A1 PCT/EP2020/080084 EP2020080084W WO2021079006A1 WO 2021079006 A1 WO2021079006 A1 WO 2021079006A1 EP 2020080084 W EP2020080084 W EP 2020080084W WO 2021079006 A1 WO2021079006 A1 WO 2021079006A1
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WO
WIPO (PCT)
Prior art keywords
pixels
lighting device
luminous intensity
automotive lighting
alternative dataset
Prior art date
Application number
PCT/EP2020/080084
Other languages
English (en)
Inventor
Yasser ALMEHIO
Hafid EL IDRISSI
Original Assignee
Valeo Vision
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 Valeo Vision filed Critical Valeo Vision
Publication of WO2021079006A1 publication Critical patent/WO2021079006A1/fr

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
    • H04N19/119—Adaptive subdivision aspects, e.g. subdivision of a picture into rectangular or non-rectangular coding blocks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/90—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using coding techniques not provided for in groups H04N19/10-H04N19/85, e.g. fractals
    • H04N19/98—Adaptive-dynamic-range coding [ADRC]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
    • H04N19/174—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a slice, e.g. a line of blocks or a group of blocks
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
    • H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
    • H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
    • H04N19/182—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being a pixel

Definitions

  • This invention is related to the field of automotive lighting devices, and more particularly, to the management of the electronic data derived from the control of the lighting sources.
  • the invention provides a solution for these problems by means of a method for managing image data according to claim 1 and an automotive lighting device according to claim 8.
  • Preferred embodiments of the invention are defined in dependent claims.
  • the invention provides a method for managing image data in an automotive lighting device, the method comprising the steps of
  • each pixel is characterized by a value related to the luminous intensity of the pixel
  • This method is aimed to manage the image data which is exchanged between a control unit and a light module.
  • the control unit is in charge of calculating the image pattern and the compression data, and may be located in any position of the automotive vehicle, not necessarily physically inside the lighting device.
  • the lighting module is aimed to provide a light pattern, either for lighting or signalling, and is located inside the lighting device.
  • the main advantage of this method is the decrease in the maximum error compared to other lossy methods which do not take into account the corrective step.
  • a previous step of providing an alternative dataset is carried out.
  • This alternative dataset may comprise a discretization and linearization of the luminous intensity values or any other step which may involve the loss of a small number of data in exchange of a significant decrease in the final data size.
  • the light pixels of the image pattern are grey scale pixels, and more particularly, the luminous intensity of each pixel is according to a scale from 0 to 255.
  • Light modules usually define the light pattern on a grey scale, where the luminous intensity is graded from 0 to 255. This is a way of quantifying the light pattern so that it becomes able to be converted into light data, and then transmitted and managed by the control unit of the vehicle.
  • the modification comprises the creation of a polygonal zone where the modified alternative dataset coincides with the values of luminous intensity of the pixels.
  • the polygonal zone comprises pixels that provide the maximum error in the step of calculating the maximum error.
  • the polygonal zone is a zone where the luminous intensity values of the alternative dataset are replaced by the original values of the pixels of the image pattern, so the error in this polygonal zone becomes zero. If the polygonal zone was extended to the whole region of the image pattern, there would not be any advantage in the compression rate, but combining some zones characterized by the alternative dataset with zones characterized by the original luminous intensity values, there is a possibility to customize the error threshold and the compression rate threshold.
  • the polygonal zone has a shape of a rectangle or a diamond.
  • This shape is particularly advantageous, since it is easy to define and is suitable for catching the error values which are located in the centre of the image pattern, where luminous intensity is higher and therefore the errors are higher as well.
  • the method further comprises the step of decompressing the compressed data.
  • the compressed data is related only to a particular portion of the image pattern.
  • This cropping step is useful when a big portion of the image is completely dark, so that the compression stage is focused only on the portion which include representative values.
  • the invention provides a lighting device comprising
  • a light module comprising a plurality of light sources
  • control unit to carry out the steps of a method according to the first inventive aspect.
  • This lighting device is able to operate with a lower bandwidth than the traditional ones.
  • the light module further comprises a processor unit, the processor unit being configured to decompress the compressed data.
  • the light sources are solid-state light sources, such as LEDs.
  • solid state refers to light emitted by solid-state electroluminescence, which uses semiconductors to convert electricity into light. Compared to incandescent lighting, solid state lighting creates visible light with reduced heat generation and less energy dissipation.
  • the typically small mass of a solid-state electronic lighting device provides for greater resistance to shock and vibration compared to brittle glass tubes/bulbs and long, thin filament wires. They also eliminate filament evaporation, potentially increasing the life span of the illumination device.
  • Some examples of these types of lighting comprise semiconductor light-emitting diodes (LEDs), organic light-emitting diodes (OLED), or polymer light-emitting diodes (PLED) as sources of illumination rather than electrical filaments, plasma or gas.
  • FIG. 1 shows a first image of the photometry of a high beam module which is projected by an automotive lighting device according to the invention.
  • FIG. 1 shows a portion of a pixel matrix representing the photometry of [Fig
  • FIG 3 shows an error map of a first lossy method which has been applied to the image pattern of [Fig 2]
  • FIG 4 shows an example of a polygonal zone used in a method according to the invention.
  • FIG 5 shows an error map of a method according to the invention, once the step of the polygonal zone has been carried out.
  • FIG. 6 shows an automotive lighting device according to the invention.
  • FIG 1 shows a first image of the photometry of a high beam module which is to be projected by an automotive lighting device according to the invention.
  • This first image may be divided into pixels and each pixel may be characterized by its luminous intensity, in a scale from 0, which would correspond to black, to 255, which would correspond to white.
  • FIG 2 shows a portion of such a pixel matrix, called image pattern 1.
  • Each pixel 11 of this image pattern 1 is characterized by a number according to the aforementioned scale.
  • the compression of this image pattern 1 according to commercially available software products would offer a compression rate lower than 50%, which is unacceptable by some car manufacturers.
  • a first lossy method is then applied to the image pattern 1.
  • These methods replace some strings of values of luminous intensity by a smaller amount of data, which represent the luminous evolution in this string. For example, a group of 20 values may be replaced by a linear approximation, to save data size.
  • the linear approximation will not usually be identical to the original values, but in some cases will provide a valid approximation, with a low error, and a significant data size saving. The higher the compression rate achieved, the higher the maximum error obtained.
  • FIG 3 shows an error map of a first lossy method which has been applied to the image pattern. This error map compares each value of luminous intensity provided by the first lossy method with the corresponding value of the original pattern of luminous intensity as in the image pattern 1. The difference is shown in this figure with a colour scale. As may be seen in the scale, the first lossy method provides a maximum error of 8 in a scale from 0 to 255, which is a good value.
  • the method of the invention further proposes the definition of a zone where the data for compressing is not taken from the first lossy method, but from the original image pattern. This decreases the compression rate, but also decreases the maximum error. The bigger the polygonal zone is, the higher will be both decreases.
  • FIG 4 shows an example of a polygonal zone 2 which is applied in a method according to the invention.
  • This polygonal zone 2 is a diamond shape zone which tries to include all the pixels which provide an error comprised between 4 and 8.
  • This diamond shape is centred in the centre of the image pattern, because it is easier that the higher error pixels are located in this zone, since it is the zone with a maximum luminous intensity.
  • FIG 5 shows an error map of the corrected method, once the step of the polygonal zone has been carried out. Inside this polygonal zone, the error is zero, and outside this polygonal zone, the error was low, so the final result is a low maximum error and a low average error.
  • the compression rate of this method is slightly lower than the compression rate achieved by the first lossy method without correction, but the average error and the maximum error are also lower. In any case, the compression rate is enough to fulfil some car manufacturers’ requests, so this compressed data may be sent to the light module compelling with restrictive conditions about the bandwidth.
  • FIG 6 shows an automotive lighting device according to the invention, this lighting device comprising: - a light module 4 comprising a plurality of LEDs 5;
  • control unit 6 to carry out the compression steps described in the previous figures, generating the compressed data
  • processor unit 7 being configured to decompress the compressed data, this processor unit being located in the light module 4.
  • This light module would achieve a very good quality projection with an improved transmission bandwidth.

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  • Engineering & Computer Science (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Lighting Device Outwards From Vehicle And Optical Signal (AREA)

Abstract

L'invention concerne un procédé de gestion de données d'image dans un dispositif d'éclairage automobile (10). Ce procédé comprend les étapes consistant à fournir un motif d'image (1) et un ensemble de données alternatif ayant un nombre de données inférieur au nombre de pixels, l'ensemble de données alternatif étant associé aux valeurs d'intensité lumineuse des pixels (11). Ensuite, l'erreur maximale est calculée et l'ensemble de données alternatif est modifié pour réduire l'erreur maximale, ce qui permet d'obtenir un ensemble de données alternatif modifié. L'ensemble de données alternatif modifié est comprimé et envoyé à un module lumineux. L'invention concerne également un dispositif d'éclairage automobile (10) pour réaliser les étapes d'un tel procédé.
PCT/EP2020/080084 2019-10-25 2020-10-26 Procédé de gestion des données d'image et dispositif d'éclairage automobile WO2021079006A1 (fr)

Applications Claiming Priority (2)

Application Number Priority Date Filing Date Title
FR1911982A FR3102631A1 (fr) 2019-10-25 2019-10-25 Procédé de gestion des données d'images et dispositif d'éclairage automobile
FRFR1911982 2019-10-25

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WO2021079006A1 true WO2021079006A1 (fr) 2021-04-29

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Citations (5)

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CN105120288A (zh) * 2010-04-13 2015-12-02 Ge视频压缩有限责任公司 解码器、编码器以及用于解码和编码的方法
US20160073025A1 (en) * 2008-01-29 2016-03-10 Enforcement Video, Llc Omnidirectional camera for use in police car event recording
US20160267325A1 (en) * 2015-03-12 2016-09-15 Qualcomm Incorporated Systems and methods for object tracking
US20180118095A1 (en) * 2015-04-10 2018-05-03 Maxell, Ltd. Image projection apparatus
US20190166338A1 (en) * 2017-11-28 2019-05-30 Jaguar Land Rover Limited Projection apparatus

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20160073025A1 (en) * 2008-01-29 2016-03-10 Enforcement Video, Llc Omnidirectional camera for use in police car event recording
CN105120288A (zh) * 2010-04-13 2015-12-02 Ge视频压缩有限责任公司 解码器、编码器以及用于解码和编码的方法
US20160267325A1 (en) * 2015-03-12 2016-09-15 Qualcomm Incorporated Systems and methods for object tracking
US20180118095A1 (en) * 2015-04-10 2018-05-03 Maxell, Ltd. Image projection apparatus
US20190166338A1 (en) * 2017-11-28 2019-05-30 Jaguar Land Rover Limited Projection apparatus

Non-Patent Citations (3)

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Title
"Embedded Vision in Advanced Driver Assistance Systems", 1 January 2014, SPRINGER, ISBN: 978-3-319-09386-4, article ZORAN NIKOLIC: "Embedded Vision in Advanced Driver Assistance Systems", pages: 45 - 69, XP055669416, DOI: 10.1007/978-3-319-09387-1_3 *
CUADROS-VARGAS A J ET AL: "Generating Segmented Quality Meshes from Images", JOURNAL OF MATHEMATICAL IMAGING AND VISION, KLUWER ACADEMIC PUBLISHERS, BO, vol. 33, no. 1, 27 June 2008 (2008-06-27), pages 11 - 23, XP019679313, ISSN: 1573-7683 *
DALAI M ET AL: "l/spl infin/ norm based second generation image coding", IMAGE PROCESSING, 2004. ICIP '04. 2004 INTERNATIONAL CONFERENCE ON SINGAPORE 24-27 OCT. 2004, PISCATAWAY, NJ, USA,IEEE, vol. 5, 24 October 2004 (2004-10-24), pages 3193 - 3196, XP010786476, ISBN: 978-0-7803-8554-2, DOI: 10.1109/ICIP.2004.1421792 *

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