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Method for identifying oil fume of range hood and range hood

A range hood and oil fume technology, which is applied in the direction of oil fume removal, character and pattern recognition, heating methods, etc., can solve the inaccurate recognition results of oil fume image data frames, the inability to accurately control kitchen appliances, and the inability to correctly calculate key feature smoke Issues such as the actual amount of change, to achieve the effect of ensuring quality and using habits

Active Publication Date: 2022-05-03
JOYOUNG CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

As a result, the image data acquired by the camera cannot correctly calculate the actual change of the key feature smoke during the working process of the equipment, so that it is impossible to accurately control the kitchen appliances
[0003] Most of the current oil fume processing algorithms are based on the premise that the image quality of the real-time oil fume data frame as an input parameter is ideal enough, but due to the large difference between the actual oil fume image data frame and the laboratory environment, it will lead to The final oil fume recognition result is inaccurate
[0004] The traditional way to deal with the above problems is usually to adjust the light intensity of the supplementary light and then send the images acquired by the camera to the algorithm processing unit for processing. When the kitchen is in a high-exposure environment, even if the oil fume is very small, a large value of the oil fume may be calculated due to the influence of the high exposure of the lens. There may be a large difference between the image after simple brightness adjustment and the actual object.

Method used

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  • Method for identifying oil fume of range hood and range hood
  • Method for identifying oil fume of range hood and range hood
  • Method for identifying oil fume of range hood and range hood

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Experimental program
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Embodiment 1

[0099] Such as Figure 4 As shown, in order to solve the impact of ambient light on image recognition, parameters such as brightness, grayscale, and color that may have a greater impact on recognition are selected. In sunny days, no direct light, and bright environments, the image effect of this embodiment is processed. The numerical range of the correct recognition result is used as the parameter benchmark, and the brightness value, color, gray value and other parameters obtained by the camera at the current moment are compared with the parameter benchmark, and when the value is not within the benchmark range, adjust the relevant parameters until the value falls. Within the reference range, the image processed by the above process is re-identified to correspond to the oil fume information, and the process is as follows:

[0100] 1. Adjust the photosensitive parameters of the hue head based on the brightness, grayscale, and color parameter benchmarks of the pre-established sta...

Embodiment 2

[0107] This embodiment illustrates the process of image brightness adjustment:

[0108] Upgrade the conventional lighting device of the range hood to a lighting with adjustable brightness value, and choose a lens with a large enough light input for the camera recognition module so that it can have better adaptability in the case of excessive light or too dark light . The brightness adjustment process in the image recognition process is as follows: Figure 5 As shown, first obtain the brightness value of the photosensitive device of the camera. If the brightness value is lower than the reference range, it means that the current ambient light is dark. At this time, the exposure time of the lens is increased step by step. The power consumption of the camera increases, and the heat of the camera makes the current noise of the captured image larger. Therefore, it is necessary to set the exposure level threshold, which can allow the camera to freely adjust the exposure time without...

Embodiment 3

[0110] This embodiment illustrates the process of image color adjustment:

[0111] After the above brightness adjustment, the brightness value of the image data collected by the cooker hood in real time has been adjusted to the reference range, but no matter how high or low the exposure parameters of the camera are adjusted or the brightness value of the captured image is directly adjusted, the image quality will be affected. And almost all image recognition technologies are based on the grayscale image after image data frame binarization, so the image quality loss caused by brightness adjustment must be restored before the grayscale image processing. The camera-side and color-related parameters include image contrast, hue, and saturation. Its adjustment process is as follows Figure 6 Shown: first obtain the image contrast, chroma and saturation values ​​of the color card area, and compare with the established color reference, so that the three parameters of the color card a...

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Abstract

A cooking fume identification method for a range hood and the range hood. The method includes: obtaining the current light state through an image acquisition device, adjusting the photosensitive parameters of the image acquisition device, so that the imaging parameter information of the image acquisition device is within the value range of the imaging parameter information in the standard light state; The acquisition device acquires target image information, and compares the acquired target image information with preset image reference information; adjusts the imaging brightness information of the range hood and / or the attribute information of the target image, so that the target The image information is within the value range of the preset image reference information; according to the adjusted target image information, the oil fume amount information corresponding to the target image is determined.

Description

technical field [0001] The invention relates to the technical field of smart home appliances, in particular to a method for identifying oil fume of a range hood and the range hood. Background technique [0002] It has become a trend in the development of the industry to use image recognition for oil fume recognition on hoods and stoves. One of the core problems of image recognition algorithm processing in the kitchen environment is that the adaptability and accuracy of the recognition algorithm cannot be guaranteed. Since the actual kitchen environment of the user is different, the same user’s kitchen environment will be different in different time periods of the year and in a day. The light intensity at different time points is not the same. It is impossible for the same set of algorithms to be suitable for all these situations. As a result, the image data acquired by the camera cannot correctly calculate the actual change of the key characteristic smoke during the operat...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): F24C15/20G06V10/141G06V20/00G06V10/75G06K9/62
CPCF24C15/2021G06V20/00G06V10/141G06F18/22
Inventor 朱泽春孙金彪
Owner JOYOUNG CO LTD
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