WO2022207582A1

WO2022207582A1 - Method for managing image data and automotive lighting device

Info

Publication number: WO2022207582A1
Application number: PCT/EP2022/058182
Authority: WO
Inventors: Yasser ALMEHIO
Original assignee: Valeo Vision
Priority date: 2021-03-31
Filing date: 2022-03-28
Publication date: 2022-10-06
Also published as: JP2024514507A; EP4315848A1; WO2022207582A9

Abstract

The invention provides a method for managing image data in an automotive lighting device (10). This method comprises the steps of providing an image pattern (1), dividing the image pattern (1) in rows or columns of pixels (2), calculating a first gradient value related to the relation between the numeric value of a first pixel and the numeric value of an adjacent pixel, checking, for each pixel, if the difference between the corresponding gradient value and the first gradient fulfils one of a first or second condition, define linear segments, compress the data of the linear segments and send the compressed data to the light module. The invention also provides an automotive lighting device (10) for performing the steps of such a method.

Description

Method for managing image data and automotive lighting device

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.

Current lighting devices comprises an increasing number of light sources which has to be controlled, to provide adaptive lighting functionalities.

This number of light sources involves a big amount of data, which has to be managed by the control unit. The CAN protocol is often used, in some of their variants (CAN-FD is one of the most used ones) to transfer data between the PCM and the light module. However, some car manufacturers decide to limit the bandwidth of the CAN protocol, and this affects the management operations, which usually requires about 5 Mbps.

Current compression methods are not very efficient for high beam patterns, and this compromises the bandwidth reduction which is requested by car manufacturers.

This problem is even worse with the modern high resolution modules, where the information amount is much higher, while the limit in the bandwidth does not increase.

A solution for this problem is sought.

The invention provides a solution for these problems by means of a method for managing image data in an automotive lighting device, the method comprising the steps of

providing an image pattern comprising a plurality of pixels, wherein each pixel is characterized by a numeric value related to the luminous intensity of the pixel;
divide the image pattern in rows or columns of pixels, thus creating a plurality of row patterns;
provide a plurality of intensity ranges, wherein the numeric values of every pixel is comprised within one and only one of the intensity ranges, wherein each intensity range has a representative value;
replace the numeric value of each pixel by the representative value of the corresponding intensity range, so that each pixel is characterized by one representative value;
finding pixels with a representative value of the pixel different from the representative value of an adjacent pixel, these pixels becoming breaking pixels;
providing, for each row pattern, a plurality of linear segments, each linear segment being comprised between two breaking pixels;
characterizing each linear segment by two characterizing values;
compressing the characterizing values; and
send the compressed data to the light module.

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 increase in the compression rate without a significant loss of quality, due to the optimization in the localization of the breaking pixels. The abovementioned method provides a fast and reliable way of extending the segment until the conditions are not met, thus providing a lower amount of data compared to the original pixels replaced thereby, especially when the image pattern is referred to a high beam pattern. The pseudo-Gaussian shape of the row patterns also contributes to the compression rate being increased, since there are some portions of the row pattern which can be replaced by a linear approximation without a significant loss in data.

In some particular embodiments, 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.

In some particular embodiments, the number of intensity ranges is comprised between 4 and 20.

A low number of intensity ranges will substantially increase the compression rate, since they will have less breaking points and they will have more chance to be linearized with less loss. A higher number of intensity ranges will increase the quality, reducing the data loss, but at the expense of reducing the compression rate.

In some particular embodiments, preceding claims, wherein the step of finding pixels comprises the substep of

finding all the pixels which have a representative value of the pixel different from the representative value of an adjacent pixel; and
select a relevant group of pixels by choosing, for each row pattern, only the pixels which have a representative value of the pixel different from the representative value of an adjacent pixel of the same row pattern.

The number of breaking points will be decisive for the equilibrium between a high compression rate but at a higher data loss and a lower compression rate but at a lower data loss. When performing the step of finding pixels with a representative value different from the representative value of an adjacent pixel, it may mean that the pixel has an adjacent pixel in the adjacent row pattern which has a different representative value. But an entire row pattern may have the same representative value. If the adjacent row pattern has a different representative value, this would provide that all the pixels of a row pattern would be selected as breaking pixels, which is not necessary. A substep of selecting the relevant breaking pixels is useful since it reduces the number of breaking pixels (increasing the compression rate) but without any further data loss, since all those breaking pixels of the same row pattern do not add any valuable information.

In some particular embodiments, the two characterizing values are the numeric value of one of the breaking pixels limiting the linear segment and the distance between the two breaking pixels limiting the linear segment.

These two values are the only essential values to define a linear approximation for the intensity values of each linear segment. The breaking points are selected as key points where the gradient of the luminous intensity suffers a substantial change. These breaking points are used to keep these changes, so that the quality of the image is not lost. To reconstruct the linear approximation, it is enough to keep the intensity value of a first breaking point (the origin of the linear segment) and the number of pixels until the next breaking point (where the linear segment ends). The value of the luminous intensity in this end of the linear segment will be provided by the intensity value of the next breaking point, which will be stored since it is the origin of the next linear segment. Thus, data is saved and the compression rate is improved.

In some particular embodiments, all the intensity ranges have the same size.

Thus, the model is consistent, since all the breaking points are selected by an equality criterion.

In some particular embodiments, the method further comprises the step of decompressing the compressed data.

This step is convenient when the original image is to be projected by the light module.

In some particular embodiments, 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.

In a second inventive aspect, the invention provides a lighting device comprising

a light module comprising a plurality of light sources; and
a 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.

In some particular embodiments, the light module further comprises a processor unit, the processor unit being configured to decompress the compressed data.

With a decompression stage in the proper light module, the bandwidth is narrowed until the module itself.

In some particular embodiments, the light sources are solid-state light sources, such as LEDs.

The term "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.

Unless otherwise defined, all terms (including technical and scientific terms) used herein are to be interpreted as is customary in the art. It will be further understood that terms in common usage should also be interpreted as is customary in the relevant art and not in an idealised or overly formal sense unless expressly so defined herein.

In this text, the term “comprises” and its derivations (such as “comprising”, etc.) should not be understood in an excluding sense, that is, these terms should not be interpreted as excluding the possibility that what is described and defined may include further elements, steps, etc.

To complete the description and in order to provide for a better understanding of the invention, a set of drawings is provided. Said drawings form an integral part of the description and illustrate an embodiment of the invention, which should not be interpreted as restricting the scope of the invention, but just as an example of how the invention can be carried out. The drawings comprise the following figures:

shows a first image of the photometry of a high beam module which is projected by an automotive lighting device according to the invention.

shows a portion of a pixel matrix representing an example of photometry.

shows a representation of a row pattern of a method according to the invention.

shows a representation of some of the steps of a method according to the invention.

shows the result of a linearization steps when a method according to the invention is used.

shows an automotive lighting device according to the invention.

In these figures, the following reference numbers have been used:

1 Image pattern

2 Row pattern

3 Pixel of the image pattern

4 Light module

5 LEDs

6 Control unit

7 Processor unit

8 Representative value

9 Boundary

10 Automotive lighting device

11 Breaking pixel

100 Automotive vehicle

The example embodiments are described in sufficient detail to enable those of ordinary skill in the art to embody and implement the systems and processes herein described. It is important to understand that embodiments can be provided in many alternate forms and should not be construed as limited to the examples set forth herein.

Accordingly, while embodiment can be modified in various ways and take on various alternative forms, specific embodiments thereof are shown in the drawings and described in detail below as examples. There is no intent to limit to the particular forms disclosed. On the contrary, all modifications, equivalents, and alternatives falling within the scope of the appended claims should be included.

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.

shows a portion of such a pixel matrix, called image pattern 1. Each pixel 3 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.

In this image, the pixels are divided into row patterns 2. Each pattern comprises a string of data, with numbers between 0 and 255, depending on the luminous intensity of the associated pixels. Obviously, the numeric values of these pixels are a simplified example, merely chosen for the sake of a better understanding of the invention, they do not correspond to the luminous intensity of the light pattern of .

shows a further step in a method according to the invention. In this step, a plurality of intensity ranges are provided to quantize the original intensity values, so that the original intensity value of each pixel is replaced by a representative value 8, so that each pixel is now characterized by one representative value 8. In the original photometry pattern, each pixel could adopt any value from 0 to 255. However, after this step, the intensity values are classified in, for example, eight different ranges

From 0 to 31, the representative value is defined as 16;
From 32 to 63, the representative value is defined as 48;
From 64 to 95, the representative value is defined as 80;
From 96 to 127, the representative value is defined as 112;
From 128 to 159, the representative value is defined as 144;
From 160 to 191, the representative value is defined as 176;
From 192 to 223, the representative value is defined as 208; and
From 224 to 255, the representative value is defined as 240.

Now, instead of 256 different values, only eight different representative values are allowed, and every pixel has one of this eight representative values: 16, 48, 80, 112, 144, 176, 208 or 240.

shows a quantized map of the light pattern after performing this step. This figure corresponds to the light map of but after being quantized in ten different intensity ranges.

This quantization step is performed just to find out the best breaking points, to perform a linearization of the original light map. The quantized map is not sent to the lighting device for its projection, it is just used as an intermediate step.

Each quantized section has a boundary 9, which is defined by pixels having a representative value of the pixel different from the representative value of an adjacent pixel.

However, this turn outs to be a high number of pixels. It is advantageous to reduce the number of pixels to choose only the most relevant ones. This is done by selecting, for this group of breaking pixels, only the pixels which have a representative value of the pixel different from the representative value of an adjacent pixel of the same row.

shows the chosen breaking pixels 11. These pixels will be used for linearizing the original light pattern (not the quantized one, the quantized one is calculated only to obtain the breaking points).

Once the breaking points are obtained, a plurality of linear segments are defined for each row. In other words, each row is divided into a plurality of linear segments. Each linear segment is defined by a start pixel and an end pixel, so that the number of pixels is known (the number of pixels between the start pixel and the end pixel). Hence, since all the segments are consecutive and adjacent, and the segments cover the totality of each row, the start value and the number of pixels is enough to define a segment, since the end value will be the same as the start value of the next segments. Therefore, only two values are needed to define each segment. The breaking points are chosen as the start points for every segment, so that in each row will be the same number of linear segments as the number of breaking points belonging to this row.

A particular embodiment of the method of the invention would comprise the step of calculating a gradient for each pixel of this row pattern.

Only these two values per segment are sent to the lighting device, in order to reconstruct a linear pattern which will be an approximation of the original light pattern shown in .

shows an automotive lighting device according to the invention, this lighting device comprising:

a light module 4 comprising a plurality of LEDs 5;
a control unit 6 to carry out the compression steps described in the previous figures, generating the compressed data; and
a processor unit 7, the 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 good quality projection with an improved transmission bandwidth.

Claims

Method for managing image data in an automotive lighting device (10), the method comprising the steps of:
providing an image pattern (1) comprising a plurality of pixels (3), wherein each pixel is characterized by a numeric value related to the luminous intensity of the pixel (3);

divide the image pattern (1) in rows or columns of pixels (2), thus creating a plurality of row patterns (2);

provide a plurality of intensity ranges, wherein the numeric values of every pixel is comprised within one and only one of the intensity ranges, wherein each intensity range has a representative value;

replace the numeric value of each pixel by the representative value of the corresponding intensity range, so that each pixel is characterized by one representative value;

finding pixels with a representative value of the pixel different from the representative value of an adjacent pixel, these pixels becoming breaking pixels;

providing, for each row pattern, a plurality of linear segments, each linear segment being comprised between two breaking pixels;

characterizing each linear segment by two characterizing values;

compressing the characterizing values; and

send the compressed data to the light module.
Method according to claim 1, wherein the light pixels (3) of the image pattern (1) are greyscale pixels, and more particularly, the luminous intensity of each pixel (3) is characterized by a number according to a scale from 0 to 255.
Method according to any of the preceding claims, wherein the number of intensity ranges is comprised between 4 and 20.
Method according to any of the preceding claims, wherein the step of finding pixels comprises the substep of
finding all the pixels which have a representative value of the pixel different from the representative value of an adjacent pixel; and

select a relevant group of pixels by choosing, for each row pattern, only the pixels which have a representative value of the pixel different from the representative value of an adjacent pixel of the same row pattern.
Method according to any of the preceding claims, wherein the two characterizing values are the numeric value of one of the breaking pixels limiting the linear segment and the distance between the two breaking pixels limiting the linear segment.
Method according to any of the preceding claims, wherein all the intensity ranges have the same size.
Method according to any of the preceding claims, further comprising the step of decompressing the compressed data.
Method according to any of the preceding claims, wherein the compressed data is related only to a particular portion of the image pattern (1).
Automotive lighting device (10) comprising:
a light module (4) comprising a plurality of light sources (5); and

a control unit (6) to carry out the steps of a method according to any of the preceding claims.
Automotive lighting device (10) according to claim 9, wherein the light module (4) further comprises a processor unit (7), the processor unit (7) being configured to decompress the compressed data.
Automotive lighting device (10) according to any of claims 9 or 10, wherein the light sources (5) are solid-state light sources, such as LEDs.