Cooking Chamber Browning Detection Using Differential Light Imaging
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Solution Overview
Problem
Existing methods for determining the degree of browning of food in cooking appliances are inaccurate and complex, particularly due to the non-linear nature of the browning process and the difficulty in distinguishing between dark and light areas, which can lead to overcooking.
Innovation Solution
A method using a camera to generate reference and measurement images at different brightness levels, creating a difference image that accounts for stray light, allowing for spatially resolved and temporally precise determination of browning progression, independent of scattered light, and enabling the use of low-resolution cameras.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If high-resolution cameras are used for browning detection, then measurement precision is improved, but device complexity and cost increase
Solution Approach 1:
The patent changes the parameter being measured from absolute color values to relative color differences. By calculating the difference between images taken at different light intensities, the system eliminates the need for high resolution while maintaining browning detection accuracy. This parameter transformation allows simple cameras to achieve precise measurement through differential measurement rather than direct high-resolution capture.
Solution Approach 2:
The patent replaces the mechanical/optical requirement of high-resolution camera hardware with a computational approach using simple image subtraction. Instead of relying on complex camera optics and sensors to resolve fine color differences, the system uses basic image processing to extract browning information from intensity differences, substituting hardware complexity with algorithmic simplicity.
2Measurement precision
If continuous monitoring is performed to accurately detect browning, then measurement precision is improved, but loss of time increases due to processing complexity
Solution Approach 1:
The patent extracts only the essential information needed for browning detection by calculating the difference between two images taken at different light intensities. This extraction of the differential signal removes unnecessary data processing while retaining the critical browning information, significantly reducing processing time compared to analyzing complete high-resolution images.
Solution Approach 2:
The patent performs a minimal necessary action by taking only two images at different intensities and computing their difference, rather than performing continuous full-image analysis. This partial action approach provides sufficient information for accurate browning detection while minimizing processing time and computational resources required.
3Device complexity
If simple cameras are used for browning detection, then device complexity is reduced, but measurement precision deteriorates due to inability to distinguish dark areas
Solution Approach 1:
The patent uses periodic action by capturing images at two different light intensity levels and computing their difference. This periodic measurement approach allows simple cameras to detect browning by comparing how different areas respond to light intensity changes, effectively compensating for the camera's limited resolution and color discrimination capabilities.
Solution Approach 2:
The patent introduces an intermediary computational step (image difference calculation) that transforms the limited data from simple cameras into meaningful browning information. By using the difference between two images as an intermediary representation, the system bridges the gap between simple camera hardware and accurate browning detection requirements.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This method provides accurate and timely identification of the degree of browning, simplifying the process and reducing costs by eliminating the need for high-resolution cameras and white balance, while allowing for automatic determination within the cooking appliance.
Implementation Method 1
a light source to illuminate the cooking chamber
Implementation Method 2
a camera directed into the cooking chamber... generating a reference difference image using the camera as the difference between a first image of the food being cooked
Data Source
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Figure 7
AI summary
The invention relates to a method for establishing a degree of browning of food to be cooked (G1-G3) in a cooking chamber (2) of a household cooking device (1), which household cooking device (1) has a camera (7) directed into the cooking chamber (2) and a light source (8) for illuminating the cooking chamber (2), and wherein a reference image is captured by means of the camera (7), a first measurement image is captured at a first brightness of the light source (8), a second measurement image is captured at a second brightness of the light source (8), a difference image (MD1, MD2) is generated from the first measurement image and the second measurement image, and the difference image is compared (BB, H) with the reference image. A household cooking device (1) has a camera (7) directed into the cooking chamber (2), a light source (8) for illuminating the cooking chamber (2), and a control device (9) coupled to the camera (7) and the light source (8), wherein the household cooking device (1) is configured for carrying out the method. The invention can be particularly advantageously applied to ovens.