Data processing method and system and cooking equipment
By acquiring and processing temperature and image information of the cooking cavity in the cooking equipment, the temperature changes in the food area can be identified, solving the problem of high resource consumption in the existing technology and achieving efficient and accurate identification of the food cooking status.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- NINGBO FOTILE KITCHEN WARE CO LTD
- Filing Date
- 2026-01-04
- Publication Date
- 2026-05-15
AI Technical Summary
Existing cooking equipment suffers from excessive resource consumption when collecting and processing large amounts of cooking data in real time, which affects the efficiency and accuracy of identifying the cooking status of ingredients.
By acquiring temperature distribution and image information of the cooking cavity, the food area is identified, and the cooking status is identified when there are significant temperature changes. By combining historical food temperature information and image processing technology, data compression and correction are performed to reduce the frequency of real-time identification.
It improves the accuracy and efficiency of food cooking status recognition, and reduces the consumption of computing resources and energy.
Smart Images
Figure CN122048814A_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of kitchen appliance technology, and in particular to a data processing method, system and cooking equipment. Background Technology
[0002] Existing cooking equipment integrates various sensors to collect relevant data on ingredients during the cooking process. In order to accurately identify the cooking status of ingredients, these sensors usually need to collect cooking data in real time and send the cooking data to the controller or server of the cooking equipment for identification of the cooking status. Since the amount of cooking data generated during the cooking process is very large, the frequent transmission, storage and identification of cooking data will lead to excessive resource consumption of the cooking equipment or server, affecting the efficiency of identifying the cooking status of ingredients. Summary of the Invention
[0003] To address the aforementioned technical issues, this application discloses a data processing method, system, and cooking equipment. The method determines the temperature change information corresponding to each pixel in the current food region image based on the current cavity temperature distribution information of the cooking equipment. When the temperature information of the food region changes significantly, the cooking state of the target food is identified based on the current food temperature information. This method can ensure the accuracy of the identification of the food cooking state and save computing resources.
[0004] On the one hand, this application provides a data processing method, the method comprising: During the cooking process of the target ingredient, the current cavity image, the current cavity temperature distribution information, and the historical ingredient temperature information of the cooking cavity are acquired; the current cavity image includes the current ingredient region image, and the current cavity temperature distribution information represents the temperature information corresponding to each pixel in the current cavity image; Based on the current cavity temperature distribution information, determine the current food temperature information corresponding to each pixel in the current food region image; Based on the historical food temperature information and the current food temperature information, the temperature change information corresponding to each pixel in the current food region image is determined. The cooking state of the target ingredient is determined based on the current ingredient temperature information corresponding to the first target pixel; the first target pixel is a pixel in the current ingredient region image where the temperature change information is greater than a preset temperature change threshold.
[0005] In some embodiments, the current cavity image further includes a current non-food region image, and determining the current food temperature information corresponding to each pixel in the current food region image based on the current cavity temperature distribution information includes: Edge detection processing is performed on the current cavity image to obtain the boundary information of the food area; The boundary information is mapped to the current cavity temperature distribution information to determine the initial food temperature information corresponding to each pixel in the current food area image, and the initial ambient temperature information corresponding to each pixel in the current non-food area image. The initial food temperature information is corrected based on the initial ambient temperature information to obtain the current food temperature information.
[0006] In some embodiments, the step of correcting the initial food temperature information based on the initial ambient temperature information to obtain the current food temperature information includes: A first confidence interval is determined based on the first mean and first variance of the initial food temperature information, and a second confidence interval is determined based on the second mean and second variance of the initial ambient temperature information. If there is an overlap between the first confidence interval and the second confidence interval, the temperature information in the initial food temperature information that exceeds the first confidence interval is replaced with the first mean to obtain the current food temperature information.
[0007] In some embodiments, after determining a first confidence interval based on the first mean and first variance of the initial food temperature information, and determining a second confidence interval based on the second mean and second variance of the initial ambient temperature information, the method further includes: If there is no overlap between the first confidence interval and the second confidence interval, the temperature information in the initial food temperature information that falls within the second confidence interval is replaced with the first mean to obtain the current food temperature information.
[0008] In some embodiments, determining the cooking state of the target ingredient based on the current ingredient temperature information corresponding to the first target pixel includes: Obtain historical food region images of the target food ingredient; The second target pixel is determined based on the historical food region image and the current food region image; The number of the first target pixels and the number of the second target pixels are weighted to obtain pixel change information; If the pixel change information is greater than a preset pixel change threshold, the cooking state of the target ingredient is determined based on the current ingredient temperature information and the current ingredient region image.
[0009] In some embodiments, determining the second target pixel based on the historical food region image and the current food region image includes: The historical food region image and the current food region image are subjected to grayscale conversion processing to obtain the historical grayscale food image and the current grayscale food image; Based on the historical grayscale food images and the current grayscale food images, determine the grayscale change information corresponding to each pixel in the current food region image; The pixels in the current food region image whose grayscale change information is greater than a preset grayscale change threshold are identified as the second target pixels.
[0010] In some embodiments, the weighted processing of the number of the first target pixels and the number of the second target pixels to obtain pixel change information includes: Temperature gradient information is determined based on the current food temperature information, and image gradient information is determined based on the current food region image. The temperature weighting coefficient and the image weighting coefficient are determined based on the temperature gradient information and the image gradient information. Based on the temperature weighting coefficient and the image weighting coefficient, the number of the first target pixels and the number of the second target pixels are weighted to obtain the pixel change information.
[0011] In some embodiments, after weighting the number of the first target pixels and the number of the second target pixels to obtain pixel change information, the method further includes: When the pixel change information is greater than the preset pixel change threshold, the current food temperature information and the current food region image are compressed to obtain compressed food temperature information and compressed food image. The temperature information and image of the compressed food are uploaded to the target server.
[0012] On the other hand, this application also provides a cooking device, the cooking device including a controller for performing the data processing method as described above.
[0013] On the other hand, this application also provides a data processing system, which includes a data acquisition terminal and a controller; The acquisition terminal is used to acquire the current cavity image and the current cavity temperature distribution information of the cooking cavity during the cooking process of the target food, and send the current cavity image and the current cavity temperature distribution information to the controller. The controller is used to execute the data processing method as described above.
[0014] Implementing the embodiments of this application has the following beneficial effects: The data processing method disclosed in this application acquires the current cavity image and current cavity temperature distribution information of the cooking cavity during the cooking process of the target ingredient. Based on the current cavity temperature distribution information, it determines the temperature change information corresponding to each pixel in the current ingredient region image included in the current cavity image. When the temperature change information corresponding to the pixel in the current ingredient region image is greater than a preset temperature change threshold, that is, when the temperature change of the pixel in the current ingredient region image is significant, the cooking state of the target ingredient is identified based on the current ingredient temperature information corresponding to the pixel with significant temperature change in the current ingredient region image. That is, it is not necessary to identify the cooking state of the target ingredient in real time, but to identify the cooking state of the target ingredient when the temperature of the ingredient region changes significantly. This can ensure the accuracy of the identification of the cooking state of the ingredient, save computing resources, reduce the energy consumption of the cooking equipment, and improve the efficiency of identifying the cooking state of the ingredient. Attached Figure Description
[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0016] Figure 1 A flowchart illustrating a data processing method provided in an embodiment of this application; Figure 2 A flowchart illustrating a method for correcting food temperature information provided in an embodiment of this application; Figure 3 A flowchart illustrating a data processing method provided in an embodiment of this application; Figure 4 This is a schematic diagram of the structure of a cooking equipment controller provided in an embodiment of this application; Figure 5 This is a schematic diagram of the hardware structure of an electronic device provided in an embodiment of this application. Detailed Implementation
[0017] To make the objectives, technical solutions, and advantages of this application clearer, the application will be further described in detail below with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.
[0018] In the description of this application, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of technical features indicated. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. Furthermore, the terms "first," "second," etc., are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such information can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in a sequence other than that illustrated or described herein.
[0019] The data processing system provided in this application includes a data acquisition terminal and a controller; the data acquisition terminal refers to the infrared imager and visible light camera of the cooking equipment, which are used to acquire infrared temperature data and visible light data, respectively; the controller refers to the controller of the cooking equipment, which can be a kitchen appliance with food cooking function such as a steamer, oven, or steam oven.
[0020] The acquisition terminal is used to acquire the current cavity image and the current cavity temperature distribution information of the cooking cavity during the cooking process of the target food ingredient, and send the current cavity image and the current cavity temperature distribution information to the controller.
[0021] The controller is configured to acquire, during the cooking process of the target ingredient, a current cavity image of the cooking cavity, current cavity temperature distribution information, and historical ingredient temperature information of the target ingredient; the current cavity image includes a current ingredient region image, and the current cavity temperature distribution information represents the temperature information corresponding to each pixel in the current cavity image; determine the current ingredient temperature information corresponding to each pixel in the current ingredient region image based on the current cavity temperature distribution information; determine the temperature change information corresponding to each pixel in the current ingredient region image based on the historical ingredient temperature information and the current ingredient temperature information; and determine the cooking state of the target ingredient based on the current ingredient temperature information corresponding to a first target pixel; the first target pixel is a pixel in the current ingredient region image whose temperature change information is greater than a preset temperature change threshold.
[0022] See Figure 1 , Figure 1 This is a flowchart illustrating a data processing method provided in an embodiment of this application. The method is applied to a controller of a cooking device and includes: S101, during the cooking process of the target ingredient, the current cavity image of the cooking cavity, the current cavity temperature distribution information, and the historical ingredient temperature information of the target ingredient are obtained; the current cavity image includes the current ingredient region image, and the current cavity temperature distribution information represents the temperature information corresponding to each pixel in the current cavity image; In some embodiments, during the cooking process of the target ingredient, an infrared imager installed in the cooking cavity collects the current cavity temperature distribution information of the cooking cavity and sends it to the controller of the cooking equipment. A visible light camera installed in the cooking cavity collects the current cavity image of the cooking cavity and sends it to the controller of the cooking equipment. The infrared imager and the visible light camera are installed on the same inner wall of the cooking cavity, which can be the top wall or the side wall. Before use, the infrared imager and the visible light camera need to be image registered and address mapped.
[0023] In some embodiments, the historical food temperature information of the target ingredient refers to the food temperature information of the target ingredient at historical times before the current time, and the historical food temperature information of the target ingredient can be stored locally on the cooking device.
[0024] In some embodiments, the current cavity image consists of two parts: the current food region image and the current non-food region image. The current cavity temperature distribution information represents the temperature information corresponding to each pixel in the current cavity image.
[0025] S103, determine the current food temperature information corresponding to each pixel in the current food region image based on the current cavity temperature distribution information; In some embodiments, the current cavity temperature distribution information can be divided into temperature information corresponding to the food area and temperature information corresponding to the non-food area based on the current cavity image. The temperature information corresponding to the food area is the current food temperature information corresponding to each pixel in the current food area image.
[0026] S105, Based on the historical food temperature information and the current food temperature information, determine the temperature change information corresponding to each pixel in the current food region image; In some embodiments, the current food temperature information refers to the temperature information corresponding to each pixel in the food region image included in the current cavity image, and the historical food temperature information refers to the temperature information corresponding to each pixel in the food region image included in the historical cavity images. The current cavity image refers to the cavity image of the current frame, and the historical cavity image refers to the cavity image of the reference frame. The reference frame refers to the frame before the current frame, such as the frame preceding the current frame. If the current frame is the first frame, there is no reference frame, and the temperature change information corresponding to each pixel in the current food region image is determined to be 0.
[0027] In some embodiments, by comparing historical food temperature information with current food temperature information, the temperature change information corresponding to each pixel in the current food region image can be determined, that is, the difference between the temperature of the pixel in the current frame food region image and the temperature of the corresponding pixel in the reference frame food region image.
[0028] S107, determine the cooking state of the target ingredient based on the current ingredient temperature information corresponding to the first target pixel; the first target pixel is a pixel in the current ingredient area image where the temperature change information is greater than a preset temperature change threshold.
[0029] In some embodiments, pixels in the current food region image whose temperature change information is greater than a preset temperature change threshold are identified as first target pixels, i.e., pixels in the current food region image with significant temperature changes. The cooking state of the target food can be determined based on the current food temperature information corresponding to the first target pixel. The preset temperature change threshold can be set according to actual needs.
[0030] In some embodiments, after determining the cooking state of the target ingredient, the current frame is determined as the reference frame.
[0031] In other embodiments, the controller of the cooking device can upload the current food temperature information corresponding to the first target pixel to the target server. That is, the temperature information of the pixels with significant temperature changes in the current food area image is uploaded to the target server, and the location information of the pixels with significant temperature changes in the current food area image is also uploaded to the target server. The target server determines the cooking status of the target food based on the temperature information and location information of the first target pixel.
[0032] In some embodiments, the current cavity image further includes a current non-food region image, and determining the current food temperature information corresponding to each pixel in the current food region image based on the current cavity temperature distribution information includes: Edge detection processing is performed on the current cavity image to obtain the boundary information of the food area; The boundary information is mapped to the current cavity temperature distribution information to determine the initial food temperature information corresponding to each pixel in the current food area image, and the initial ambient temperature information corresponding to each pixel in the current non-food area image. The initial food temperature information is corrected based on the initial ambient temperature information to obtain the current food temperature information.
[0033] In some embodiments, by performing edge detection processing on the current cavity image, the boundary information of the food region, i.e. the boundary coordinates of the food region, can be obtained, thereby distinguishing the current food region image and the current non-food region image in the current cavity image. Then, the boundary information is mapped to the current cavity temperature distribution information to determine the current temperature information corresponding to the food region (i.e., the initial food temperature information corresponding to each pixel in the current food region image) and the current temperature information corresponding to the non-food region (i.e., the initial ambient temperature information corresponding to each pixel in the current non-food region image).
[0034] In some embodiments, due to the irregular shape of the target food and the limited edge detection accuracy, the initial food temperature information may contain temperature information corresponding to some non-food areas, such as the temperature information of some metal materials like trays. The introduction of the temperature information of the metal materials will affect the subsequent recognition of the cooking state of the target food. Therefore, it is necessary to correct the initial food temperature information based on the initial ambient temperature information to obtain the current food temperature information, that is, the corrected temperature information corresponding to each pixel in the current food area image.
[0035] This embodiment of the application can distinguish between the current food area image and the current non-food area image by performing edge detection processing on the current cavity image. Then, based on the current cavity temperature distribution information, it can determine the initial food temperature information corresponding to the food area and the initial ambient temperature information corresponding to the non-food area. Then, it can correct the initial food temperature information based on the initial ambient temperature information to obtain the current food temperature information. By correcting the current temperature information corresponding to the food area, it can avoid the interference of the temperature information of the metal material in the non-food area, improve the accuracy of the current temperature information corresponding to the food area, and thus improve the accuracy of identifying the cooking state of the target food.
[0036] In some embodiments, see Figure 2 , Figure 2 This is a flowchart illustrating a method for correcting food temperature information according to an embodiment of this application. The step of correcting the initial food temperature information based on the initial ambient temperature information to obtain the current food temperature information includes: S201, a first confidence interval is determined based on the first mean and the first variance of the initial food temperature information, and a second confidence interval is determined based on the second mean and the second variance of the initial ambient temperature information; In some embodiments, a first confidence interval corresponding to the food region can be obtained based on the first mean and first variance of the initial food temperature information, and a second confidence interval corresponding to the non-food region can be obtained based on the second mean and second variance of the initial ambient temperature information.
[0037] S203, if there is an overlap between the first confidence interval and the second confidence interval, replace the temperature information in the initial food temperature information that exceeds the first confidence interval with the first mean value to obtain the current food temperature information.
[0038] In some embodiments, when there is an overlap between the first confidence interval and the second confidence interval, i.e., the temperature characteristics of the food area are similar to those of the non-food area, the temperature values in the current temperature information corresponding to the food area that exceed the first confidence interval are removed, and the average of the current temperature information corresponding to the food area, i.e., the first average, is used instead.
[0039] S205, if there is no overlap between the first confidence interval and the second confidence interval, replace the temperature information in the initial food temperature information that is within the second confidence interval with the first mean to obtain the current food temperature information.
[0040] In some embodiments, when there is no overlap between the first confidence interval and the second confidence interval, i.e., when there is a significant difference between the temperature characteristics of the food area and the temperature characteristics of the non-food area, the temperature values in the second confidence interval of the current temperature information corresponding to the food area are removed, and replaced with the mean of the current temperature information corresponding to the food area, i.e., the first mean.
[0041] This application embodiment determines the initial food temperature information corresponding to the food area and the initial ambient temperature information corresponding to the non-food area based on the current cavity temperature distribution information. Then, it corrects the initial food temperature information based on the temperature characteristics of the food area and the non-food area to obtain the current food temperature information. By correcting the current temperature information corresponding to the food area, the interference of the temperature information of the metal material in the non-food area can be avoided, improving the accuracy of the current temperature information corresponding to the food area, and thus improving the accuracy of identifying the cooking state of the target food.
[0042] In some embodiments, see Figure 3 , Figure 3 This is a flowchart illustrating a data processing method provided in an embodiment of this application. The step of determining the cooking state of the target ingredient based on the current ingredient temperature information corresponding to the first target pixel includes: S301, Obtain a historical food region image of the target food ingredient; In some embodiments, the historical food region image of the target food refers to the food region image included in the historical cavity image, and the historical food region image of the target food can be stored locally on the cooking device.
[0043] S303, determine the second target pixel based on the historical food region image and the current food region image; In some embodiments, by comparing historical food region images with current food region images, pixels where image information has changed significantly can be identified, i.e., second target pixels.
[0044] S305, perform weighted processing on the number of the first target pixels and the number of the second target pixels to obtain pixel change information; In some embodiments, temperature gradient information is determined based on the current food temperature information, image gradient information is determined based on the current food region image, temperature weight coefficient and image weight coefficient are determined based on the temperature gradient information and image gradient information, and the number of first target pixels and the number of second target pixels are weighted based on the temperature weight coefficient and image weight coefficient to obtain pixel change information.
[0045] S307, if the pixel change information is greater than a preset pixel change threshold, determine the cooking state of the target ingredient based on the current ingredient temperature information and the current ingredient region image.
[0046] In some embodiments, when the pixel change information is greater than a preset pixel change threshold, i.e., when the temperature information and image information of the food area change significantly, the cooking state of the target food is determined based on the current food temperature information and the current food area image. The preset pixel change threshold can be set according to actual needs.
[0047] In the cooking process of the target ingredient, this application's embodiments determine the number of image change pixels based on historical and current ingredient area images, the number of temperature change pixels based on historical and current ingredient temperature information, and the pixel change information based on the number of image change pixels and temperature change pixels. When the pixel change information exceeds a preset pixel change threshold, the cooking state of the target ingredient is determined based on the current ingredient temperature information and the current ingredient area image. That is, it is not necessary to identify the cooking state of the target ingredient in real time, but to identify the cooking state of the target ingredient only when the temperature information and image information of the ingredient area change significantly. This can ensure the accuracy of the identification of the ingredient's cooking state, save computing resources, reduce the energy consumption of cooking equipment, and improve the efficiency of identifying the ingredient's cooking state.
[0048] In some embodiments, determining the second target pixel based on the historical food region image and the current food region image includes: The historical food region image and the current food region image are subjected to grayscale conversion processing to obtain the historical grayscale food image and the current grayscale food image; Based on the historical grayscale food images and the current grayscale food images, determine the grayscale change information corresponding to each pixel in the current food region image; The pixels in the current food region image whose grayscale change information is greater than a preset grayscale change threshold are identified as the second target pixels.
[0049] In some embodiments, grayscale conversion is performed on the historical food region image and the current food region image to obtain the historical grayscale food image corresponding to the historical food region image and the current grayscale food image corresponding to the current food region image. Then, by comparing the historical grayscale food image and the current grayscale food image, the grayscale change information corresponding to each pixel in the current food region image is determined, that is, the difference between the grayscale value of the pixel in the current frame grayscale food image and the grayscale value of the corresponding pixel in the reference frame grayscale food image. Then, the pixels in the current food region image whose grayscale change information is greater than a preset grayscale change threshold are determined as the second target pixels. The preset grayscale change threshold can be set according to actual needs.
[0050] In this embodiment, during the cooking process of the target ingredient, a first target pixel is determined based on historical and current ingredient temperature information, and a second target pixel is determined based on historical and current ingredient region images. Then, pixel change information is determined based on the first and second target pixels. If the pixel change information is greater than a preset pixel change threshold, the cooking state of the target ingredient is determined based on the current ingredient temperature information and the current ingredient region image. That is, it is not necessary to identify the cooking state of the target ingredient in real time, but to identify the cooking state of the target ingredient only when the temperature information and image information of the ingredient region change significantly. This can ensure the accuracy of the identification of the cooking state of the ingredient, save computing resources, reduce the energy consumption of cooking equipment, and improve the efficiency of identifying the cooking state of the ingredient.
[0051] In some embodiments, the weighted processing of the number of the first target pixels and the number of the second target pixels to obtain pixel change information includes: Temperature gradient information is determined based on the current food temperature information, and image gradient information is determined based on the current food region image. The temperature weighting coefficient and the image weighting coefficient are determined based on the temperature gradient information and the image gradient information. Based on the temperature weighting coefficient and the image weighting coefficient, the number of the first target pixels and the number of the second target pixels are weighted to obtain the pixel change information.
[0052] In some embodiments, the degree of temperature and image variation differs for different cooking stages or different types of ingredients. Therefore, weighting coefficients can be dynamically calculated based on the gradient information of temperature and image. Specifically, the horizontal gradient of each pixel in the current ingredient region image is calculated based on the current ingredient temperature information corresponding to each pixel. Vertical gradient of each pixel and the gradient norm of each pixel. Then the mean gradient norm of temperature is Similarly, the mean gradient norm of the image is... The weighting coefficients are dynamically calculated based on the mean gradient norm, with temperature as the weighting coefficient. Then pixel change information = ,in, The number of the first target pixels. This represents the number of pixels in the second target area.
[0053] This application embodiment determines temperature weighting coefficients and image weighting coefficients based on temperature gradient information and image gradient information. Based on the temperature weighting coefficients and image weighting coefficients, the number of first target pixels and the number of second target pixels are weighted to obtain pixel change information. For different cooking stages or different types of ingredients, it can accurately determine whether the temperature information and image information of the ingredient area have changed significantly.
[0054] In some embodiments, after weighting the number of the first target pixels and the number of the second target pixels to obtain pixel change information, the method further includes: When the pixel change information is greater than the preset pixel change threshold, the current food temperature information and the current food region image are compressed to obtain compressed food temperature information and compressed food image. The temperature information and image of the compressed food are uploaded to the target server.
[0055] In some embodiments, when the pixel change information is greater than a preset pixel change threshold, the current food temperature information and the current food region image can be compressed to obtain compressed food temperature information and compressed food image. The compressed food temperature information and compressed food image are then uploaded to the target server, and the target server determines the cooking status of the target food based on the compressed food temperature information and compressed food image.
[0056] In some embodiments, before data compression, the highest and lowest temperatures of the food area are determined, and the temperature difference is calculated. If the difference is less than 12.8°C, a byte is added to the data packet header to indicate the 4-1 byte encoding method, specifically storing the first raw value of each line. (4 bytes) Calculate the difference between the subsequent data in this row and the first original value. (1 byte). If the difference is greater than 12.8°, add one byte before the data packet to indicate the 4-2 byte encoding method, specifically storing the first raw value of each line. (4 bytes), using 2 bytes to represent the interpolation between the subsequent data in the row and the first original value.
[0057] In some embodiments, compressed food images are uploaded to the target server in h264 format.
[0058] In this embodiment, when the temperature and image information of the food area change significantly, the current food temperature information and the current food area image are compressed. The compressed temperature data and image data are then uploaded to the target server. In other words, data is actively uploaded only when a significant change in food temperature or texture is detected. This reduces the data upload frequency while ensuring the accuracy of cooking status recognition. In addition, redundant data is reduced by removing data from non-food areas. Data compression reduces data throughput and server resource utilization.
[0059] This application provides a data processing method, the method comprising: during the cooking process of a target ingredient, acquiring a current cavity image of a cooking cavity, current cavity temperature distribution information, and historical ingredient temperature information of the target ingredient; the current cavity image includes a current ingredient region image, and the current cavity temperature distribution information characterizes the temperature information corresponding to each pixel in the current cavity image; determining the current ingredient temperature information corresponding to each pixel in the current ingredient region image based on the current cavity temperature distribution information; determining the temperature change information corresponding to each pixel in the current ingredient region image based on the historical ingredient temperature information and the current ingredient temperature information; determining the cooking state of the target ingredient based on the current ingredient temperature information corresponding to a first target pixel; the first target pixel being a pixel in the current ingredient region image whose temperature change information is greater than a preset temperature change threshold. In this embodiment, during the cooking process of the target ingredient, the current cavity image and current cavity temperature distribution information of the cooking cavity are acquired. Based on the current cavity temperature distribution information, the temperature change information corresponding to each pixel in the current ingredient region image included in the current cavity image is determined. When the temperature change information corresponding to the pixel in the current ingredient region image is greater than a preset temperature change threshold, that is, when the temperature change of the pixel in the current ingredient region image is significant, the cooking state of the target ingredient is identified based on the current ingredient temperature information corresponding to the pixel with significant temperature change in the current ingredient region image. That is, it is not necessary to identify the cooking state of the target ingredient in real time, but to identify the cooking state of the target ingredient when the temperature of the ingredient region changes significantly. This can ensure the accuracy of the identification of the cooking state of the ingredient, save computing resources, reduce the energy consumption of the cooking equipment, and improve the efficiency of identifying the cooking state of the ingredient.
[0060] This application also provides a cooking device, see [link to relevant documentation] Figure 4 The cooking device includes a controller, the controller comprising: The data acquisition module 410 is used to acquire the current cavity image of the cooking cavity, the current cavity temperature distribution information, and the historical temperature information of the target ingredient during the cooking process of the target ingredient; the current cavity image includes the current ingredient area image, and the current cavity temperature distribution information represents the temperature information corresponding to each pixel in the current cavity image; The current food temperature information determination module 420 is used to determine the current food temperature information corresponding to each pixel in the current food region image based on the current cavity temperature distribution information; Temperature change information determination module 430 is used to determine the temperature change information corresponding to each pixel in the current food region image based on the historical food temperature information and the current food temperature information. The cooking state determination module 440 is used to determine the cooking state of the target ingredient based on the current ingredient temperature information corresponding to the first target pixel; the first target pixel is a pixel in the current ingredient region image where the temperature change information is greater than a preset temperature change threshold.
[0061] In some embodiments, the current cavity image further includes a current non-food area image, and the current food temperature information determination module 420 includes: An edge detection unit is used to perform edge detection processing on the current cavity image to obtain the boundary information of the food region; An initial temperature information determination unit is used to map the boundary information to the current cavity temperature distribution information, determine the initial food temperature information corresponding to each pixel in the current food area image, and the initial ambient temperature information corresponding to each pixel in the current non-food area image. The food temperature information correction unit is used to correct the initial food temperature information based on the initial ambient temperature information to obtain the current food temperature information.
[0062] In some embodiments, the food temperature information correction unit includes: The confidence interval determination subunit is used to determine a first confidence interval based on the first mean and the first variance of the initial food temperature information, and to determine a second confidence interval based on the second mean and the second variance of the initial ambient temperature information. The first correction subunit is used to replace the temperature information in the initial food temperature information that exceeds the first confidence interval with the first mean value when there is an overlap between the first confidence interval and the second confidence interval, so as to obtain the current food temperature information.
[0063] In some embodiments, the food temperature information correction unit further includes: The second correction subunit is used to replace the temperature information in the initial food temperature information that is within the second confidence interval with the first mean value when there is no overlap between the first confidence interval and the second confidence interval, so as to obtain the current food temperature information.
[0064] In some embodiments, the cooking state determination module 440 includes: A historical food ingredient region image acquisition unit is used to acquire historical food ingredient region images of the target food ingredient; The second target pixel determination unit is used to determine the second target pixel based on the historical food region image and the current food region image. The pixel change information determination unit is used to perform weighted processing on the number of the first target pixels and the number of the second target pixels to obtain pixel change information; The cooking state determination unit is used to determine the cooking state of the target ingredient based on the current ingredient temperature information and the current ingredient region image when the pixel change information is greater than a preset pixel change threshold.
[0065] In some embodiments, the second target pixel determination unit includes: The grayscale conversion subunit is used to perform grayscale conversion processing on the historical food region image and the current food region image to obtain the historical grayscale food image and the current grayscale food image. The grayscale change information determination subunit is used to determine the grayscale change information corresponding to each pixel in the current food region image based on the historical grayscale food image and the current grayscale food image. The second target pixel determination subunit is used to determine the pixels in the current food region image whose grayscale change information is greater than a preset grayscale change threshold as the second target pixel.
[0066] In some embodiments, the pixel change information determination unit includes: The gradient information determination subunit is used to determine temperature gradient information based on the current food temperature information and to determine image gradient information based on the current food region image. The weighting coefficient determination subunit is used to determine the temperature weighting coefficient and the image weighting coefficient based on the temperature gradient information and the image gradient information. The pixel change information determination subunit is used to perform weighted processing on the number of the first target pixels and the number of the second target pixels based on the temperature weight coefficient and the image weight coefficient to obtain the pixel change information.
[0067] In some embodiments, the cooking state determination module 440 further includes: The data compression unit is used to perform data compression processing on the current food temperature information and the current food region image when the pixel change information is greater than the preset pixel change threshold, so as to obtain compressed food temperature information and compressed food image. The data uploading unit is used to upload the temperature information of the compressed food and the image of the compressed food to the target server.
[0068] The apparatus provided in the above embodiments can execute the method provided in any embodiment of this application, and has the corresponding functional modules and beneficial effects for executing the method. Technical details not described in detail in the above embodiments can be found in a data processing method provided in any embodiment of this application.
[0069] This embodiment also provides a computer-readable storage medium storing computer-executable instructions, which are loaded by a processor and executed by the data processing method described above in this embodiment.
[0070] This embodiment also provides an electronic device, which includes a processor and a memory, wherein the memory stores a computer program adapted to be loaded by the processor and executed as described above in this embodiment of a data processing method.
[0071] The electronic device may be a computer terminal, a mobile terminal, or a server, and may also participate in constituting the apparatus or system provided in the embodiments of this application. For example... Figure 5 As shown, the electronic device 5 may include one or more (shown as 502a, 502b, ..., 502n in the figure) processors 502 (processors 502 may include, but are not limited to, microprocessors MCUs or programmable logic devices FPLDs), a memory 504 for storing information, and a transmission device 506 for communication functions. In addition, it may also include input / output interfaces (I / O interfaces) and network interfaces. Those skilled in the art will understand that... Figure 5 The structure shown is for illustrative purposes only and does not limit the structure of the aforementioned electronic device. For example, electronic device 5 may also include... Figure 5 The more or fewer components shown, or having the same Figure 5 The different configurations shown.
[0072] It should be noted that the aforementioned one or more processors 502 and / or other information processing circuits are generally referred to herein as "information processing circuits". These information processing circuits may be wholly or partially embodied in software, hardware, firmware, or any other combination thereof. Furthermore, the information processing circuits may be a single, independent processing module, or may be wholly or partially integrated into any other element in the electronic device 5.
[0073] The memory 504 can be used to store software programs and modules of application software, such as the program instruction / information storage device corresponding to the method described in the embodiments of this application. The processor 502 executes various functional applications and information processing by running the software programs and modules stored in the memory 504, thereby realizing the above-mentioned data processing method. The memory 504 may include high-speed random access memory, and may also include non-volatile memory, such as one or more magnetic storage devices, flash memory, or other non-volatile solid-state memory. In some instances, the memory 504 may further include memory remotely located relative to the processor 502, and these remote memories can be connected to the electronic device 5 via a network. Examples of the above-mentioned networks include, but are not limited to, the Internet, corporate intranets, local area networks, mobile communication networks, and combinations thereof.
[0074] The transmission device 506 is used to receive or send information via a network. Specific examples of the network described above may include a wireless network provided by the communication provider of the electronic device 5. In one example, the transmission device 506 includes a Network Interface Controller (NIC), which can connect to other network devices via a base station to communicate with the Internet. In another example, the transmission device 506 may be a Radio Frequency (RF) module, used for wireless communication with the Internet.
[0075] This specification provides the operational steps of the methods described in the embodiments or flowcharts, but more or fewer operational steps may be included based on conventional or non-inventive labor. The steps and order listed in the embodiments are merely one possible execution order among many steps and do not represent the only execution order. In actual system or interrupt product execution, the methods shown in the embodiments or drawings can be executed sequentially or in parallel (e.g., in a parallel processor or multi-threaded processing environment).
[0076] The structure shown in this embodiment is only a partial structure related to the solution of this application and does not constitute a limitation on the device to which the solution of this application is applied. Specific devices may include more or fewer components than shown, or combinations of certain components, or arrangements of different components. It should be understood that the methods, apparatuses, etc., disclosed in this embodiment can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of modules is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection between devices or unit modules through some interfaces.
[0077] Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.
[0078] Those skilled in the art will further recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed in this specification can be implemented in electronic hardware, computer software, or a combination of both. To clearly illustrate the interchangeability of hardware and software, the components and steps of each example have been generally described in terms of functionality in the foregoing description. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.
[0079] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application.
Claims
1. A data processing method, characterized in that, The method includes: During the cooking process of the target ingredient, the current cavity image, the current cavity temperature distribution information, and the historical ingredient temperature information of the cooking cavity are acquired; the current cavity image includes the current ingredient region image, and the current cavity temperature distribution information represents the temperature information corresponding to each pixel in the current cavity image; Based on the current cavity temperature distribution information, determine the current food temperature information corresponding to each pixel in the current food region image; Based on the historical food temperature information and the current food temperature information, the temperature change information corresponding to each pixel in the current food region image is determined. The cooking state of the target ingredient is determined based on the current ingredient temperature information corresponding to the first target pixel; the first target pixel is a pixel in the current ingredient region image where the temperature change information is greater than a preset temperature change threshold.
2. The data processing method according to claim 1, characterized in that, The current cavity image also includes the current non-food region image. Determining the current food temperature information corresponding to each pixel in the current food region image based on the current cavity temperature distribution information includes: Edge detection processing is performed on the current cavity image to obtain the boundary information of the food area; The boundary information is mapped to the current cavity temperature distribution information to determine the initial food temperature information corresponding to each pixel in the current food area image, and the initial ambient temperature information corresponding to each pixel in the current non-food area image. The initial food temperature information is corrected based on the initial ambient temperature information to obtain the current food temperature information.
3. The data processing method according to claim 2, characterized in that, The step of correcting the initial food temperature information based on the initial ambient temperature information to obtain the current food temperature information includes: A first confidence interval is determined based on the first mean and first variance of the initial food temperature information, and a second confidence interval is determined based on the second mean and second variance of the initial ambient temperature information. If there is an overlap between the first confidence interval and the second confidence interval, the temperature information in the initial food temperature information that exceeds the first confidence interval is replaced with the first mean to obtain the current food temperature information.
4. The data processing method according to claim 3, characterized in that, After determining a first confidence interval based on the first mean and first variance of the initial food temperature information, and determining a second confidence interval based on the second mean and second variance of the initial ambient temperature information, the method further includes: If there is no overlap between the first confidence interval and the second confidence interval, the temperature information in the initial food temperature information that falls within the second confidence interval is replaced with the first mean to obtain the current food temperature information.
5. The data processing method according to claim 1, characterized in that, Determining the cooking state of the target ingredient based on the current ingredient temperature information corresponding to the first target pixel includes: Obtain historical food region images of the target food ingredient; The second target pixel is determined based on the historical food region image and the current food region image; The number of the first target pixels and the number of the second target pixels are weighted to obtain pixel change information; If the pixel change information is greater than a preset pixel change threshold, the cooking state of the target ingredient is determined based on the current ingredient temperature information and the current ingredient region image.
6. The data processing method according to claim 5, characterized in that, The step of determining the second target pixel based on the historical food region image and the current food region image includes: The historical food region image and the current food region image are subjected to grayscale conversion processing to obtain the historical grayscale food image and the current grayscale food image; Based on the historical grayscale food images and the current grayscale food images, determine the grayscale change information corresponding to each pixel in the current food region image; The pixels in the current food region image whose grayscale change information is greater than a preset grayscale change threshold are identified as the second target pixels.
7. The data processing method according to claim 5, characterized in that, The step of weighting the number of the first target pixels and the number of the second target pixels to obtain pixel change information includes: Temperature gradient information is determined based on the current food temperature information, and image gradient information is determined based on the current food region image. The temperature weighting coefficient and the image weighting coefficient are determined based on the temperature gradient information and the image gradient information. Based on the temperature weighting coefficient and the image weighting coefficient, the number of the first target pixels and the number of the second target pixels are weighted to obtain the pixel change information.
8. The data processing method according to claim 5, characterized in that, After weighting the number of the first target pixels and the number of the second target pixels to obtain pixel change information, the method further includes: When the pixel change information is greater than the preset pixel change threshold, the current food temperature information and the current food region image are compressed to obtain compressed food temperature information and compressed food image. The temperature information and image of the compressed food are uploaded to the target server.
9. A cooking device, characterized in that, The cooking device includes a controller for performing the data processing method as described in any one of claims 1-8.
10. A data processing system, characterized in that, The system includes a data acquisition terminal and a controller; The acquisition terminal is used to acquire the current cavity image and the current cavity temperature distribution information of the cooking cavity during the cooking process of the target food, and send the current cavity image and the current cavity temperature distribution information to the controller. The controller is configured to perform the data processing method as described in any one of claims 1-8.