Operation of a household cooking appliance having at least one camera

Abstract

A method (S1-S4) for operating a domestic cooking appliance (1), the cooking appliance having a cooking chamber (2) and at least one camera (5), the at least one camera being arranged to record a pixel-based image (10) from the cooking chamber (2), wherein (a) at least one image (10) is recorded (S1) from the cooking chamber (2) by means of the at least one camera (5), and (b) the image (10) is evaluated (S2-S4) excluding brightness values ​​of relevant pixels of the image. A domestic cooking appliance (1) having a cooking chamber (2) and at least one camera (5) for recording a pixel-based image (12), wherein the domestic cooking appliance (1) is designed to carry out the method (S1-S4). The invention is particularly advantageously applicable to ovens, microwave ovens, steam processing devices or any combination thereof.

Description

Technical Field

[0001] The invention relates to a method for operating a domestic cooking appliance, the domestic cooking appliance having a cooking chamber and at least one camera, the at least one camera being arranged to record pixel-based images from the cooking chamber, in which method at least one image is recorded from the cooking chamber by means of the at least one camera and the image is evaluated. The invention also relates to a domestic cooking appliance having a cooking chamber and at least one camera for recording pixel-based images, wherein the domestic cooking appliance is designed to carry out the method. The invention can be applied particularly advantageously to ovens, microwave ovens, steam processing devices or any combination thereof. Background Art

[0002] DE 10 2016 215 550 A1 discloses a method for determining the degree of browning of food cooked in a cooking chamber of a domestic cooking appliance, the domestic cooking appliance having a camera pointing toward the cooking chamber and a light source for illuminating the cooking chamber, wherein a reference image is recorded by means of the camera, a first measurement image is recorded at a first brightness of the light source, a second measurement image is recorded at a second brightness of the light source, a difference image is generated from the first measurement image and the second measurement image, and the difference image is compared with the reference image. A domestic cooking appliance having a camera pointing toward the cooking chamber, a light source for illuminating the cooking chamber, and a control device coupled to the camera and the light source, wherein the domestic cooking appliance is configured to carry out the method.

[0003] DE 10 2005 014 713 A1 discloses a sensor device having a data processing unit for determining the degree of browning of a cooked food arranged in a cooking chamber and having at least one sensor for detecting the intensity of radiation reflected by the cooked food. In order to provide a sensor device for a cooking appliance, by means of which the degree of browning of the cooked food can be determined safely, reliably and in particular independently of the size and shape of the cooked food, it is proposed that the data processing unit is used to determine a relevant parameter of a characteristic variable of the detected radiation intensity as a function of the time course of the detected radiation intensity.

[0004] WO 2014 / 053002 A2 provides a device for characterizing food color properties. The device includes a light source arranged to emit light having at least two wavelengths or wavelength ranges. The light source is also arranged to deflect light onto the surface of at least one food. The device also includes a detector positioned to detect at least a portion of the reflected light and arranged to generate an output indicating the intensity of the detected reflected light. The device is arranged so as to generate corresponding instructions for the at least two wavelengths or wavelength ranges. The relationship between the instructions for one wavelength or wavelength range in the at least two wavelengths or wavelength ranges and the instructions for another or another wavelength or wavelength range in the at least two wavelengths or wavelength ranges indicates the color properties of the food surface.

[0005] DE 10 2017 206 056 A1 discloses a method for operating a cooking appliance, wherein a cooking chamber is illuminated with light of different wavelength ranges and the light from the cooking chamber is measured, wherein the measurement results are evaluated spectroscopically and the operation of the cooking appliance is changed depending on the result of the spectroscopic evaluation. A cooking appliance is configured to run the method and comprises a cooking chamber, at least one light source for radiating light into the cooking chamber and at least one light sensor for measuring the light reflected in the cooking chamber, wherein the cooking appliance further comprises an evaluation device for spectroscopically evaluating the measurement result determined by the at least one light sensor, and a control device for controlling a cooking process depending on the result of the evaluation.

[0006] EP 0 682 243 A1 discloses an apparatus and method for measuring the browning degree of cooked food, in particular baked food, the apparatus comprising at least one radiation source generating measuring radiation and reference radiation in different wavelength ranges, the reflection and backscattering of the measuring radiation and the reference radiation being differently affected by the browning degree of the cooked food, the reflection and the backscattering both being radiated onto the cooked food through an optical device, a measuring sensor for detecting radiation emitted by the cooked food, a reference sensor for detecting the intensities of the measuring radiation and the reference radiation, and means for determining the browning degree based on the intensity of the measuring radiation detected by the measuring sensor, the intensity of the reference radiation detected by the measuring sensor, the intensity of the measuring radiation detected by the reference sensor, and the intensity of the reference radiation detected by the reference sensor.

[0007] JP 61265429 A discloses a method in which the surface of a cooking food is irradiated with two kinds of light having different wavelengths respectively while heating, and the reflected light is detected by a photometer. The food is heated by a heating device and irradiated with light sources having different emission wavelengths so that the light reflected by the food is detected by means of the photometer sensitive to the two emission wavelengths. The emission intensity of the first light source reaches its maximum value of 300 W at a wavelength of 600 nm, while the emission intensity of the second light source reaches its maximum value of 700 W at a wavelength of 1200 nm. The surface state of the cooking food can be determined by the light beam. Therefore, by presetting the detection level of the reflected light suitable for the cooking menu, cooking that always shows a good done state can be achieved. Summary of the invention

[0008] The object of the present invention is to at least partially overcome the disadvantages of the prior art and in particular to provide an improved possibility for operating a domestic cooking appliance based on an image evaluation of the cooking chamber contents.

[0009] This object is achieved according to the features of the independent claims. Advantageous embodiments are the subject matter of the dependent claims, the description and the drawings.

[0010] This object is achieved by a method for operating a domestic cooking appliance, the cooking appliance having a cooking chamber and at least one camera, the at least one camera being configured to record pixel-based images from the cooking chamber, wherein (a) at least one image is recorded from the cooking chamber by means of the at least one camera, and (b) the image is evaluated excluding brightness values ​​of relevant pixels of the image.

[0011] The method results in the advantage that the image data recorded from the cooking chamber can be evaluated largely independently of the brightness distribution in the cooking chamber, which is produced, for example, by the cooking chamber lighting and / or the incidence of ambient light. In other words, the problem of the typically uneven brightness distribution in the cooking chamber for image evaluation is solved by means of the method. In particular, the evaluation is advantageously independent of the shelf level and the height of the cooked food. The advantage is also achieved of greater robustness against brightness changes caused by the light source, which are produced, for example, by operating temperature, age of the light source and / or by varying light incident through the cooking chamber door. Furthermore, the method is advantageously largely independent of structural changes in the lighting device, for example the number and / or arrangement of the light sources for illuminating the cooking chamber. Furthermore, the advantage results that the image evaluation can be performed more simply and more quickly, in particular by reducing the amount of data to be evaluated.

[0012] The domestic cooking appliance can be in particular an oven, a microwave oven, a steaming device or any combination thereof, for example an oven with an additional microwave function and / or a steaming function. The cooking chamber can also be referred to as a muffle oven or oven. The domestic cooking appliance can have one or more cooking chambers, for example in the form of a double oven with two cooking chambers arranged one above the other.

[0013] One development consists in that the cooking chamber has a plurality of shelf levels for positioning cooking food supports such as grids, baking trays, etc. The cooking chamber typically has a delivery opening which is arranged at the front and can be closed by means of a cooking chamber door.

[0014] The at least one camera records pixel-based images, wherein each pixel is assigned a plurality of color space coordinates or associated values ​​of the color space coordinates. This can also be expressed as the image having a plurality of color space channels (hereinafter also referred to as "channels"), which represent possible color space coordinates.

[0015] One development is that the camera is a color camera. In this case, a plurality of colors or color space channels are assigned to the pixels of the recorded color image, for example red, green and blue in the case of an RGB image.

[0016] One development is that the camera is a black and white camera which records a series of a plurality of (1-channel) images at the shortest possible intervals, wherein the individual images are illuminated using different light colors, for example red, green and blue light. The individual (1-channel) images of the series can be connected and then viewed as a color image.

[0017] If there is food to be cooked in the cooking chamber, the at least one recorded image typically shows the food to be cooked (e.g. one or more distributed dishes) and usually also shows areas of the cooking chamber, such as a cooking chamber wall. In one embodiment, image areas that do not show food to be cooked may not be taken into account for the evaluation. For this purpose, for example, object recognition of the food to be cooked may be performed. The identification of image areas containing food to be cooked and image areas that do not show food to be cooked but, for example, show a cooking chamber wall is known in principle and therefore will not be explained in detail here.

[0018] In one development, at least one cooking chamber camera is arranged in the upper half of the cooking chamber in order to be able to record the cooked food particularly comprehensively. In particular, the at least one cooking chamber camera can be arranged in the ceiling region, in the left side wall region, in the right side wall region, in the rear wall region and / or in the cooking chamber door region. By way of example, a cooking chamber camera can be arranged in the ceiling region of the cooking chamber, while a further cooking chamber camera can be arranged in the upper third or quarter of the left side wall or right side wall.

[0019] One development is that the domestic cooking appliance has at least one lighting device for illuminating the cooking chamber, which lighting device comprises, for example, one or more light sources, in particular light emitters. In principle, these light sources can be arranged arbitrarily relative to the cooking chamber, for example in the top plate, in the upper half of the cooking chamber side walls (left wall, right wall, rear wall), in the cooking chamber door, etc. In particular, at least one light source can be arranged near the camera.

[0020] An image evaluation can then be performed excluding brightness values ​​of pixels of at least one recorded image, for example to determine browning of one or more dishes.

[0021] One development is that the brightness value is not taken into account for the evaluation and is therefore excluded, but is still present in the image data of the evaluated image. This can be advantageous, for example, if the image is additionally provided for display to a user on a screen.

[0022] Based on the evaluation or based on the result of the evaluation, the household cooking appliance can trigger at least one action, such as adapting the cooking process (e.g. the cooking chamber temperature) to the identified degree of doneness, determining and, if necessary, displaying the remaining operating time, interrupting the cooking process, outputting instructions to a user and / or switching to another cooking phase (e.g. a keeping warm phase), etc.

[0023] One design consists in that in step (b) a sub-step (b1) is performed: an image is generated from the recorded image (hereinafter referred to as a "brightness-normalized" image without limiting the generality), in which the brightness values ​​of the relevant pixels have been separated out, and a sub-step (b2) is performed: the brightness-normalized image is evaluated. As a result, the brightness-normalized image no longer has brightness information. This results in the following advantage: the amount of data and therefore the requirement for computing power required for the evaluation can be significantly reduced.

[0024] One design is that in step (b1), the brightness-normalized image is generated from an image whose pixels each have a plurality of color space coordinates including a brightness coordinate by separating out the brightness coordinate. This makes it particularly easy to separate or exclude brightness values ​​by simply eliminating the brightness coordinate. In other words, the channel representing the brightness coordinate ("brightness channel") has been eliminated in the brightness-normalized image. Therefore, in order to implement this design, the image or its pixels from which the brightness-normalized image is generated are described by a color space having brightness as its own color space coordinate. The remaining color space coordinates of the brightness-normalized image are also referred to as "color coordinates" hereinafter. The color coordinates then span a brightness-normalized color space. The specific value tuples of the color coordinates can then be mapped to chromaticity coordinates of the brightness-normalized color space.

[0025] One embodiment is that the brightness-normalized image is generated by eliminating the brightness channel from the HSX image. This results in the following advantages: HSX images use a widespread color space representation, which can also be easily evaluated. In addition, the image data volume can be reduced by the data volume of the brightness channel. An HSX image is understood in particular to be an image whose color space coordinates include a color value (English: "hue", hue), a color saturation (English: "saturation", saturation) and a brightness value. Alternatively, the brightness-normalized image can be generated by eliminating the brightness channel from an image that is present in a YUV format, a YIQ format, etc.

[0026] Color values ​​can be represented or described as color angles on a color wheel (e.g., 0° for red, 120° for green, and 240° for blue). Color saturation can be represented as a percentage value corresponding to an interval from zero to one (e.g., 0%=neutral gray, 50%=slightly saturated color, 100%=saturated pure color). Color value and color saturation form two color coordinates that create, for example, a circular brightness-normalized (H, S) color space.

[0027] HSX images can exist in several variants (where X = V, L, B, or I) that differ in the representation of brightness values, for example as

[0028] -HSV images, where brightness values ​​(English: "value", also called blackness value) are expressed as percentage values ​​corresponding to the interval from zero to one (0% = no brightness, 100% = full brightness);

[0029] -HSL images that use relative brightness (English: "lightness") instead of brightness values;

[0030] -HSB images with absolute brightness instead of brightness values;

[0031] -HSI images use light intensity instead of brightness values.

[0032] Since the luminance channel X is eliminated, all variants of HSX images can be used in the same way.

[0033] One design is that the pixels of the image recorded in step (a) do not have independent brightness coordinates, and in step (b1), the recorded image is converted into an image whose pixels each have a plurality of color space coordinates including brightness coordinates. This advantageously makes it possible to exclude or eliminate brightness values ​​or brightness information from the recorded image without an independent brightness channel in a relatively simple manner.

[0034] One design consists in recording an RGB image or a CMYK image in step (a) and first converting the RGB image or CMYK image into an HSX image in step (b1) and then generating the brightness-standardized ("HS") image from the HSX image by separating out the brightness values. The following advantage is achieved: the method can be performed using color images that are usually generated by a color camera in RGB format or CMYK format. The conversion into HSX images is generally known, for example according to the formulas of Gonzalez and Woods, Foley and Van Dam or Travis for the conversion from RGB to HSV. By using HSX images, the amount of data can be reduced by one third compared to RGB images and even by half compared to CMYK images.

[0035] However, the method is not limited to use with RGB images, CMYK images, HSX images, etc.

[0036] One design is to evaluate the image based on at least one remaining color coordinate, for example based on the color value of a brightness-normalized HSX image or HS image, the color saturation, or a chromaticity coordinate determined by the color value and the color saturation, to determine the doneness of the cooked food (i.e., one or more different cooked foods) imaged in the image.

[0037] One development is that the degree of doneness of the cooked food is determined by evaluating individual pixels or groups of pixels of the cooked food in the brightness-normalized image. This allows the location dependency or spatial distribution of the degree of doneness to be taken into account.

[0038] One development is that the doneness of the cooked food is determined by calculating the overall color coordinate of the cooked food. This can be performed, for example, by averaging (if necessary weighted) the value of at least one color coordinate value of a pixel belonging to the cooked food.

[0039] Doneness can generally be understood as a measurement variable that maps or represents different cooking states with two endpoints of "uncooked" and "done". In the present case, the change in doneness is identified by determining the color change on the surface of the cooked food. Therefore, the current color and / or color change is a quantifiable indication of doneness.

[0040] One extension is that the degree of doneness is a degree of browning. In contrast to the previously used method of determining the degree of browning based on the increasing darkening of the cooked food, in the present case the degree of browning can be determined, for example, based on a color change, for example a color change from a non-brown color such as green to brown. In the case of HS images, this corresponds to a change in the chromaticity coordinates in the (H, S) plane, for example from green (H=120°; S=100%) to brown (H=20°; S=75%). However, other degrees of doneness can also be determined instead of the degree of browning. Thus, a specific cooked food loses its color as the degree of doneness increases, or may change to a non-brown color as the degree of doneness increases. This is taken into account, for example, in the case where the type of cooked food is known in advance, for example based on user input or automatically determined.

[0041] The degree of doneness or reaching a target degree of doneness can be determined over the entire surface of the cooked food ("globally") or separately for different sub-regions of the cooked food ("locally"). Specifically, when the degree of doneness is determined locally, at least one action can be triggered by the cooking appliance if the target degree of doneness has been reached in one sub-region, multiple sub-regions or all sub-regions.

[0042] One embodiment is to determine that the target doneness of the food under consideration has been reached by reaching a target color point defined by the remaining color coordinates or its surroundings (e.g., target H ± 2° and target S ± 5%). This makes it particularly easy to determine the finished cooking state of the food under consideration. In an extension, the target doneness can be set before or at the beginning of the cooking process. For example, if a specific dish (e.g., chicken, pizza, casserole, etc.) and a desired degree of browning (e.g., "crispy") are set within the scope of a cooking program, the target color point corresponding to the target doneness, in particular the target degree of browning, can be calculated or called up from a data memory.

[0043] One embodiment is that steps (a) and (b) are performed multiple times in succession. This advantageously allows the color coordinates of the cooked food or the surface of the cooked food to be evaluated at different times and thus allows dynamic effects to be taken into account. In particular, the color coordinates of the cooked food determined in succession in time can be evaluated to determine a target doneness and / or a remaining cooking time for the cooked food.

[0044] One development is to evaluate temporally successive color coordinates pixel by pixel, for example by image comparison. For example, a difference image can be generated and evaluated to determine a target doneness and / or a remaining cooking time. Reaching the target doneness can then be determined, for example based on the fact that the temporal change in the color coordinates of at least 70% of the pixels is below a certain threshold and, if necessary, these pixels are within a certain distance from the target doneness.

[0045] One design is to evaluate the curve course of at least one color coordinate in order to determine the target doneness and / or the remaining cooking time of the cooked food. This makes it possible to advantageously evaluate the cooked food state (e.g. doneness, in particular browning) particularly flexibly and reliably. To evaluate the time course, known methods for curve evaluation or curve analysis can be used, such as determining maximum and / or minimum points, saddle points, high gradient points, etc. In the example case of an HSX image, the curve course can, for example, include a time change of a standardized or non-standardized color angle of a color value and / or a standardized or non-standardized change of saturation.

[0046] The object is also achieved by a domestic cooking appliance having a cooking chamber and at least one camera for recording pixel-based images, wherein the domestic cooking appliance is designed to carry out the method described above. The domestic cooking appliance can be designed similarly to the method and has the same advantages.

[0047] The evaluation can be performed in the domestic cooking appliance or outside the domestic cooking appliance (for example in an external data processing device such as a network server or a cloud computer). In the case of an evaluation in the domestic cooking appliance, the domestic cooking appliance has a corresponding data processing device and in the case of an external evaluation has a communication interface with an external data processing device. In principle, the method can also be performed in any manner distributed between the domestic cooking appliance and the external data processing device. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] The above-mentioned characteristics, features and advantages of the present invention and the manner of achieving them can be more clearly and specifically understood in conjunction with the following illustrative description of embodiments, which will be explained in more detail in conjunction with the accompanying drawings.

[0049] Figure 1 A sketch of a domestic cooking appliance having at least one camera is shown in a cross-sectional view in side view;

[0050] Figure 2 A graph showing the dependence of the mean values ​​of different color space coordinates of the HSV image of a white reference on the shelf height;

[0051] Figure 3 The standard deviation of different color coordinates of the HSV image of the white reference is shown as a function of the shelf height;

[0052] Figure 4 The graph shows the curve change process of the standardized color coordinates of the HSV image of the cooked food during the cooking operation;

[0053] Figure 5The method sequence is shown for preparing an evaluation of recorded images for operating a domestic cooking appliance. DETAILED DESCRIPTION

[0054] Figure 1 The sketch of a domestic cooking appliance 1 is shown in a sectional view from the side, which has a cooking chamber 2, whose front feed opening 3 can be closed by means of a cooking chamber door 4. The cooking chamber 2 has a plurality of shelf levels with corresponding shelf heights EH1 to EH4, wherein the shelf height EH1 is close to the floor of the cooking chamber 2 and the shelf height EH4 is close to the ceiling of the cooking chamber 2. Here, the food to be cooked A, which itself has a certain height, is placed on a second shelf height EH2, for example on a grid or a baking tray (not shown) used in the relevant shelf level.

[0055] A color camera 5 is installed in the ceiling of the cooking chamber 2 , but other cameras (not shown) may also be present. The color camera 5 is configured (ie constructed and arranged) to record a pixel-based color image from above or diagonally above the cooking chamber 2 .

[0056] The domestic cooking appliance 1 also has at least one lighting device for illuminating the cooking chamber 2, for example, a radiator (for example, LED radiator) 6 in the region of the ceiling and a radiator (for example, LED radiator) 7 in the region of the left and / or right wall of the cooking chamber 2. The brightness distribution generated in the cooking chamber 2 during operation of the radiators 6, 7 due to their light cones is non-uniform in the horizontal plane and also depends on the height measured in the cooking chamber 2. Overall, a non-uniform light distribution is generated in the cooking chamber in all three spatial directions.

[0057] The color camera 5 and the emitters 6 , 7 are connected to a control device 8 , which can also be designed as a data evaluation device.

[0058] The control device 8 can also be connected to a communication module 9 (e.g. an Ethernet module, a WLAN module, etc.) and via the communication module 9 (e.g. via a network N) to a computer C outside the device. This makes it possible to outsource data processing processes or computing power completely or partially from the domestic cooking appliance 1, for example to provide it in the so-called cloud.

[0059] Figure 2A diagram showing the average values ​​of the pixel-related values ​​of the different color space coordinates or channels H (color value), S (saturation) and V (brightness) of the HSV image of the white reference as a function of the shelf heights EH1 to EH4 is shown. The color space coordinates H, S and V are normalized here to a maximum value of "1" as follows: the color value H is normalized to 360° (a normalized color value H=0 therefore corresponds to a color angle of 0° or 360°, a color value of 0.5 corresponds to a color angle of 180°, etc.), while the color space coordinates S and V are normalized to 100% (so that a normalized value of 0.5 corresponds to a saturation of 50% or a brightness of 50%, etc.).

[0060] The HSV image may be recorded directly or indirectly (eg via an RGB image).

[0061] For shelf heights EH1 to EH4, the average value in pixels or area of ​​the white reference of the H and S channels H, S is almost constant, whereas the V channel V varies drastically.

[0062] Figure 3 Shown from Figure 2 Dependence of the standard deviations of the different color coordinates or channels H, S, V of the HSV image on the shelf heights EH1 to EH4. The standard deviation in the V channel V is significantly larger than the standard deviations in the H and S channels H, S. This means that the H and S values ​​of the individual pixels at the corresponding shelf heights EH1 to EH4 are almost constant within the area of ​​the white reference.

[0063] As a result, the browning assessment of the cooked food A taking into account the brightness may result in significant errors, especially if the shelf heights EH1 to EH4 and the height and shape of the cooked food are unknown.

[0064] Figure 4 The HSV image of the upper side of the cooked food A in the form of pizza Mozzarella is shown in a manner similar to Figure 2 The curve course of the color coordinates H and S standardized in a manner as shown in FIG. 1 during the duration t of the oven cooking operation in seconds.

[0065] Starting from about t = 800s, the values ​​of H (lower curve) and V (upper curve) begin to change significantly, with H decreasing and S increasing. Thereafter, after t = about 1200 seconds, these curves or curve changes turn into corresponding plateau states. This change in H and S corresponds to the browning of the pizza surface, so that the browning can be reliably identified even without considering the brightness value S.

[0066] The reaching of the target doneness and / or the remaining cooking time can be determined from the curves or curve changes of H and S. For example, if the time point until the start of browning and / or until the end of browning is known, the time point until the reaching of the target doneness and / or the remaining cooking time can be found through a table or characteristic curve determined experimentally, for example.

[0067] Figure 5 The method sequence is shown for preparing an evaluation of the RGB image 10 recorded by the camera 5 in step S1 for operating the domestic cooking appliance 1. For example, in order to reduce errors in the browning evaluation, highly erroneous brightness information is ignored or excluded from further evaluation.

[0068] For this purpose, in step S2 the acquired RGB image 10 with its channels R (red), G (green) and B (blue) is converted or transformed into an HSV image 11 with its channels H, S and V.

[0069] In step S3, the V channel is separated out, thereby generating a brightness-normalized HS image 12, the data volume of which is approximately one third less than that of the HSV image 11. The V channel V is therefore not used for further evaluation in step S4, as indicated by its deletion symbol.

[0070] Steps S2 , S3 and / or S4 can be executed completely or partially on the control device 8 and / or the computer C.

[0071] Of course, the invention is not limited to the embodiments shown.

[0072] In general, unless expressly excluded, for example by expressions such as "exactly one", "a", etc., are to be understood as being singular or plural, in particular in the sense of "at least one" or "one or more", etc. Numerical specifications may also include exactly the specified number as well as the usual tolerance range, unless this is expressly excluded.

[0073] Reference numerals list

[0074] 1 Household cooking utensils

[0075] 2 Cooking room

[0076] 3 Delivery opening

[0077] 4 Cooking cabinet door

[0078] 5. Color Camera

[0079] 6 Radiators

[0080] 7 Radiator

[0081] 8 Control device

[0082] 9 Communication module

[0083] 10 RGB images

[0084] 11 HSV Image

[0085] 12 Brightness normalized HS image

[0086] A. Cooking food

[0087] BB Channel

[0088] C Computer

[0089] EH1-EH4 Shelf Height

[0090] GG Channel

[0091] HH Channel

[0092] N Network

[0093] RR channel

[0094] SS Channel

[0095] VV channel.

Claims

1. A method for operating a domestic cooking appliance (1), the cooking appliance having a cooking chamber (2) and at least one camera (5), the at least one camera being arranged to record a pixel-based image (10) from the cooking chamber (2), wherein (a) at least one image (10) is recorded from the cooking chamber (2) by means of the at least one camera (5), and (b) the image (10) is evaluated excluding brightness values ​​of associated pixels of the image (10).

2. The method of claim 1, wherein step (b) comprises the sub-step (b1) generating a brightness normalized image (12) from the recorded image (10) in which the brightness values ​​of the associated pixels have been separated, and (b2) Evaluating the brightness normalized image (12).

3. The method according to claim 2, wherein in step (b1) the brightness-normalized image (12) is generated from an image whose pixels each have a plurality of color space coordinates (H, S, V) including a brightness coordinate (V), by separating the brightness coordinate (V).

4. The method according to claim 3, wherein in step (b1) the brightness normalized image (12) is generated from an HSX image (11).

5. The method according to any one of claims 3 to 4, wherein - the pixels of the image (10) recorded in step (a) do not have independent brightness coordinates, and - In step (b1), the recorded image (10) is converted into an image whose pixels each have a plurality of color space coordinates (H, S, V) including a brightness coordinate (V).

6. The method according to claim 5, wherein in step (a) an RGB image is recorded and in step (b1) the RGB image is first converted into an HSX image (11), and then the brightness-normalized image (12) is generated from the HSX image (11) by separating out the brightness values.

7. The method according to claim 3, wherein the brightness normalized image (12) is evaluated based on at least one remaining color space coordinate (H, S) to determine the doneness of the cooked food (A) imaged in the brightness normalized image (12).

8. The method according to claim 7, wherein the reaching of the target doneness of the cooked food (A) is determined by reaching a target color point defined by the remaining color coordinates (H, S) of the cooked food (A) or an environment of the target color point.

9. The method according to any one of claims 3 to 4, wherein steps (a) and (b) are performed multiple times in succession in time, and the color coordinates of the cooked food (A) in succession in time are evaluated to determine the target doneness and / or remaining cooking time of the cooked food (A). 10 . The method according to claim 9 , wherein the curve profile of at least one color coordinate (H, S) is evaluated in order to determine the target degree of doneness and / or the remaining cooking time of the cooked food (A).

11. The method of claim 7, wherein the degree of doneness is a degree of browning.

12. A domestic cooking appliance (1) having a cooking chamber (2) and at least one camera (5) for recording pixel-based images (10), wherein the domestic cooking appliance (1) is designed to carry out the method according to any of the preceding claims.

Images