Food material state identification and display framework and food material state identification and display method thereof

Abstract

The invention relates to a food material state identification and display framework and a food material state identification and display method applied to the framework. The framework comprises a camera and light source module, a processing module and a display interface. The camera and light source module is used for facing a food material storage environment and shooting at least one food material in a visible light wave band, a near-infrared light wave band and a short-wave infrared light wave band so as to generate food material shooting results respectively. The processing module is used for receiving the food material photographing results, processing and analyzing the food material photographing results through an image identification program, a plant growth index formula, a plant growth water content formula and a plant growth degree analysis formula, and then generating at least one piece of corresponding food material state information and transmitting the food material state information. The display interface is used for displaying the corresponding at least one piece of food material state information for watching.

Description

Technical Field

[0001] The present invention is a food state identification and display framework and a food state identification and display method applied thereto, and in particular, a framework and a method thereof for analyzing food photography results using a vegetation index formula, a vegetation water content formula and a vegetation degree analysis formula. Background Art

[0002] In today's busy business environment, people often have to go out to prepare their three meals a day. But even so, many people still choose to cook at home, or at least store some ingredients at home for emergency use. In this case, refrigerators with freezing and fresh-keeping functions have become the best equipment for modern people to store fish, meat, vegetables, fruits and other related ingredients or food.

[0003] With the development of science and technology, the most advanced refrigerators now not only provide the freezing and preservation functions of traditional refrigerators that maintain low temperatures, but can also further provide information as so-called smart refrigerators.

[0004] Specifically, when people store food or ingredients in the refrigerator, they often forget when they put them in, and naturally it is not easy to understand their freshness. However, this type of smart refrigerator can provide users with information about the status of food or ingredients by integrating relevant photography, detection and network transmission technologies, so that users do not have to rely solely on their own observation or memory to notice whether the food or ingredients have deteriorated, thereby achieving the purpose of preventing waste.

[0005] However, most current smart refrigerators require multiple camera lenses (i.e., color cameras) or multiple sensors with microwave or infrared light sensing functions (non-color cameras) to capture visible light or infrared light images of ingredients or food for analysis, which increases production costs. In addition, current analysis technologies for vegetable ingredients or food are also prone to affecting the accuracy of freshness judgment due to differences in their types or colors.

[0006] Therefore, how to further improve these technologies so that people can understand the status of stored ingredients or food more effectively and accurately is the main purpose of the development of this case. Summary of the invention

[0007] The purpose of the present invention is to provide a food state identification and display framework and a food state identification and display method applied thereto. The framework and the method use a vegetation index formula, a vegetation water content formula and a vegetation degree analysis formula to analyze food photography results, thereby having a good and correct effect on the freshness, state or authenticity of vegetable and fruit ingredients.

[0008] The present invention is a food state identification and display architecture, comprising a camera and light source module, a processing module and a display interface. The camera and light source module is used to face a food storage environment and photograph at least one food in the food storage environment using a visible light band, a near infrared light band and a short-wave infrared light band to generate a food photography result. The processing module is used to receive the food photography results, and process and analyze the food photography results by an image recognition program, a vegetation index formula, a vegetation water content formula and a vegetation degree analysis formula, and then generate corresponding at least one food state information and transmit it. The display interface is used to receive and display the corresponding at least one food state information for viewing.

[0009] Another aspect of the present invention is a method for identifying and displaying food status, which is applied to a food status identification and display architecture, the architecture including a camera and light source module, a processing module and a display interface, the method including the following steps: directing the camera and light source module toward a food storage environment and photographing at least one food in the food storage environment using a visible light band, a near infrared light band and a short-wave infrared light band respectively to generate a food photography result for each food; causing the processing module to receive the food photography results, and processing and analyzing the food photography results using an image recognition program, a vegetation index formula, a vegetation moisture content formula and a vegetation degree analysis formula, thereby generating corresponding at least one food status information and transmitting it; and causing the display interface to receive and display the corresponding at least one food status information for viewing.

[0010] In order to better understand the above and other aspects of the present invention, embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] Figure 1 Schematic diagram of a functional block diagram of a food status identification and display architecture 100 proposed by the present invention.

[0012] Figure 2 FIG. 1 is a schematic diagram of an application of the food status identification and display architecture 100 proposed by the present invention.

[0013] Figure 3 It is a flow chart of the implementation of the food status identification and display method proposed by the present invention in a preferred embodiment.

[0014] The reference numerals are described as follows:

[0015] 100: Food status identification and display architecture

[0016] 10: Refrigerator

[0017] 11: Food storage environment

[0018] 12: Camera and light source module

[0019] 120: Camera

[0020] 121: Visible light source

[0021] 122: Near infrared light source

[0022] 123: Short-wave infrared light source

[0023] 13: Processing module

[0024] 14: Network transmission module

[0025] 20: User device

[0026] 21: Display interface

[0027] 31: Vegetables

[0028] 32: Fruit

[0029] S1~S3: Steps DETAILED DESCRIPTION

[0030] The following embodiments are provided for detailed description. The embodiments are only used as examples and do not limit the scope of the invention. In addition, the drawings in the embodiments omit unnecessary elements or elements that can be completed by conventional techniques to clearly show the technical features of the invention.

[0031] The food state identification and display architecture and the food state identification and display method applied thereto proposed by the present invention are now described in detail with reference to a preferred embodiment. Figure 1 and Figure 2 ,in Figure 1 A functional block diagram of a food status identification and display architecture 100 proposed in the preferred embodiment; Figure 2 FIG. 1 is a schematic diagram of an application of the food status identification and display architecture 100. Figure 1 and Figure 2 As shown, the architecture 100 includes a refrigerator 10, a camera and light source module 12 and a user device 20, wherein a food storage environment 11 is formed in the refrigerator 10, the food storage environment 11 provides food storage, and the camera and light source module 12 is arranged in the refrigerator in a manner of facing the food storage environment 11.

[0032] Secondly, in order to operate the food state identification and display function of the present invention, the architecture 100 further includes a processing module 13, a network transmission module 14 and a display interface 21. In this embodiment, the processing module 13 and the network transmission module 14 are disposed in the refrigerator 10, and the processing module 13 is signal-connected to the camera and light source module 12 and the network transmission module 14 to receive, process and analyze the photographic results of the camera and light source module 12, and transmit the corresponding food state information generated after processing and analysis through the network transmission module 14.

[0033] As mentioned above, in this embodiment, the display interface 21 is a screen, which is arranged on the user device 20, and the user device 20 can be an electronic device with relevant network transmission function and processing function, such as a smart phone, a tablet computer, a desktop computer or a wearable electronic device, so that the corresponding food status information sent from the network transmission module 14 of the refrigerator 10 can be received and displayed on the display interface 21 for the user to watch. The network transmission method can be wired network transmission or wireless network transmission, depending on the electronic device used.

[0034] One feature of the present invention is that the camera and light source module 12 includes a plurality of light sources 121-123 and a camera 120, wherein a lens of the camera 120 is a wide-angle lens module or a fisheye lens module, so that photography can be performed with a larger viewing angle or a larger photographing range, so that the camera and light source module 12 can capture the overall image of the food storage environment 11 regardless of where it is located in the refrigerator 10.

[0035] like Figure 2 As shown, the food stored in the food storage environment 11 is schematically illustrated by a vegetable 31 and a fruit 32. In addition, another feature of the present invention is that the camera and light source module 12 used can photograph the stored food with a visible light band, a near infrared light (NIR) band and a short wave infrared light (SWIR) band, and each generates a food photography result, that is, including a visible light image signal, a near infrared light image signal and a short wave infrared light image signal.

[0036] As mentioned above, in this embodiment, in order to achieve the above-mentioned photography function with multiple wavebands, the camera and light source module 12 is designed to have a visible light source 121, a near infrared light source 122 and a short wave infrared light source 123, and the camera 120 has a lens, a visible light sensor chip, a near infrared light sensor chip and a short wave infrared light sensor chip (this part is not shown in the figure), so that the visible light waveband, the near infrared light waveband and the short wave infrared light waveband can be used for photography and sensing to produce the food photography results. The near infrared light waveband is light with a wavelength of about 850 to 940 nanometers (nm), and the short wave infrared light waveband is light with a wavelength of about 1200 to 1500 nanometers (nm).

[0037] In detail, when sensing, the visible light source 121, the near-infrared light source 122 and the short-wave infrared light source 123 will emit in a specific order, for example, in the order of a white light beam, a near-infrared light beam and a short-wave infrared light beam, and then the visible light sensing chip, the near-infrared light sensing chip and the short-wave infrared light sensing chip will sequentially receive the light beams reflected from the foods to obtain the food photography results, that is, the visible light image signal, the near-infrared light image signal and the short-wave infrared light image signal.

[0038] In addition to the above-mentioned solutions, the present invention can also adopt other designs to achieve the same or similar short-wave infrared light (SWIR) sensing effect. For example, in other embodiments, the camera and light source module 12 can also be directly designed using a single chip (Hyperspectral camera), that is, the camera and light source module 12 is designed to have a multi-band sensing chip with integrated sensing functions in the visible light band, the near infrared light band, and the short-wave infrared light band, and the visible light image signal, the near infrared light image signal, and the short-wave infrared light image signal are generated through the sensing of such a chip.

[0039] Another feature of the present invention is that after receiving the food photography results, the processing module 13 can access and execute the relevant firmware or program code to process and analyze the food photography results with an image recognition program, a vegetation index (or Normalized Difference Vegetation Index, referred to as NDVI) formula, a vegetation water content (or Normalized Difference Water Index, referred to as NDWI) formula and a vegetation degree analysis formula, thereby generating at least one corresponding food status information and transmitting it. In detail, the food status identification and display method of the present invention is particularly designed to provide a method for identifying the freshness or status (such as good or bad bruises, rot, dehydration, etc.) of vegetable and fruit ingredients.

[0040] See also Figure 3 , is a flowchart of the implementation of the food state identification and display method of the present invention in the preferred embodiment. First, the camera and light source module 12 is directed toward the food storage environment 11 and photographs the at least one food with a visible light band, a near infrared light band, and a short-wave infrared light band to generate a food photography result (step S1); secondly, the processing module 13 receives the food photography results, and processes and analyzes the food photography results by an image recognition program, a vegetation index formula, a vegetation water content formula, and a vegetation degree analysis formula, thereby generating corresponding at least one food state information and transmitting it (step S2); then, the display interface 21 receives and displays the corresponding at least one food state information for viewing (step S3).

[0041] The implementation content of step S1 is as described in the above paragraph, that is, the food photography results include the visible light image signal, the near infrared light image signal and the short-wave infrared light image signal, and the visible light image signal includes a red light image signal, a green light image signal and a blue light image signal. In this embodiment, the visible light image signal is used to identify the freshness or state of vegetables and fruits.

[0042] In step S2, the image recognition program is to load the visible light image signal, and perform image correction, capture and classification of the visible light image signal into one or more regions of interest (ROI) in a predetermined mode, and determine the corresponding food name of the image content. In detail, the image recognition program is a method of using current artificial intelligence technology and pattern recognition technology to perform real-time object detection and deep learning, and can identify the object of the captured image result.

[0043] In this embodiment, the predetermined mode may be a YOLO (You Only Look Once) mode, a ResNet-50 (Deep Residual Neural Network) mode, or a CNN (Convolutional Neural Networks) mode. In addition, since the camera and light source module 12 uses a wide-angle lens or a fisheye lens to take photos with a larger viewing angle or a larger range, the image captured may be distorted or distorted at the edge. Therefore, the image flattening correction can be performed through image processing to restore a shape close to the real shape. Then, the predetermined mode can be used to capture the image of the area of ​​interest of the image content, so that one or more meaningful targets to be identified can be classified. Finally, the targets to be identified in these areas of interest are identified and it is determined what kind of food they are.

[0044] For step S2, the vegetation index formula is the result of dividing the value of the near-infrared image signal minus the red light image signal by the value of the near-infrared image signal plus the red light image signal, and is defined as a vegetation index. Specifically, assuming that the near-infrared image signal is NIR, the red light image signal is RED, and the vegetation index is NDVI, the above relationship can be written as the following mathematical formula:

[0045]

[0046] As mentioned above, the near-infrared light image signal and the red light image signal are designed to have the same size, such as 8 bits or 16 bits, so that the signals can be added and subtracted. The size of the image signal is related to the scale of the image sensing that the camera and light source module 12 can perform. From formula (1), it can be seen that the vegetation index NDVI is a value not exceeding 1 (i.e., between -1 and 1), and according to the current technology for the application of the vegetation index formula, when the vegetation index NDVI is closer to 1, it means that the chlorophyll is more, that is, the better the vegetation condition; conversely, when the vegetation index NDVI is farther away from 1, it means that the chlorophyll is less, that is, the worse the vegetation condition.

[0047] Therefore, when the NDVI is within a specified range from the value 1, the corresponding food status information is set to have content representing that the food status is fresh; when the NDVI is beyond the specified range from the value 1, the corresponding food status information is set to have content representing that the food status is not fresh. The specified range can be set according to the application situation or actual needs, that is, the degree to which the NDVI is close to 1.

[0048] In terms of practical applications, Figure 2 The vegetables 31 may be, for example, Chinese cabbage, water spinach, sweet potato leaves, etc., and the vegetation index formula may be used to provide effective and appropriate food state identification.

[0049] For step S2, the plant water content formula is the result of subtracting the short-wave infrared light image signal from the near-infrared light image signal and dividing it by the value of the near-infrared light image signal plus the short-wave infrared light image signal, and is defined as a plant water content. Specifically, assuming that the near-infrared light image signal is NIR, the short-wave infrared light image signal is SWIR, and the plant water content is NDWI, the above relationship can be written as the following mathematical formula:

[0050]

[0051] As mentioned above, similarly, the near-infrared light image signal and the short-wave infrared light image signal are designed to have the same size, so that the signals can be added and subtracted. From formula (2), it can be seen that the vegetation moisture content NDWI is a value not exceeding 1 (i.e., between -1 and 1), and according to the application of the vegetation moisture content formula in the current technology, when the vegetation moisture content NDWI is closer to 1, it means that the moisture content is more, that is, the better the vegetation condition; conversely, when the vegetation moisture content NDWI is farther away from 1, it means that the moisture content is less, that is, the worse the vegetation condition.

[0052] Therefore, when the NDWI of the plant water content is within a specified range from the value 1, the corresponding food status information is set to have content representing that the food status is fresh; when the NDWI of the plant water content is beyond the specified range from the value 1, the corresponding food status information is set to have content representing that the food status is not fresh. The specified range can be set according to the application situation or actual needs, that is, the degree to which the NDWI of the plant water content is close to 1.

[0053] In terms of practical applications, Figure 2 The fruit 32 may be, for example, apples, cantaloupe, watermelons, etc., and the plant water content formula may be used to provide effective and appropriate food state identification.

[0054] The above implementation can be performed after the name or type of the food is identified, and then the state can be identified using a suitable formula. For example, if the food is a vegetable 31, the vegetation index formula can be used for state identification; if the food is a fruit 32, the vegetation water content formula can be used for state identification. However, the concept of the present invention is not limited to this. In other embodiments, the above two formulas can also be used simultaneously to identify the state of the same food.

[0055] It is understandable that, for vegetables, when the food has more chlorophyll, its water content should also be more; or, when the food is fresher, its chlorophyll and water content should both be more. In other words, for the state identification result of the same food, the vegetation index NDVI and the vegetation water content NDWI should be positively correlated. Therefore, the design of the vegetation degree analysis formula is to check the correlation between the obtained vegetation index NDVI and the vegetation water content NDWI, so as to confirm the applicability of the generated food state information.

[0056] As mentioned above, the vegetation degree analysis formula is to use the vegetation index NDVI and the vegetation water content NDWI to perform a correlation analysis, and define the result as a vegetation degree. In detail, the content of the vegetation index NDVI and the vegetation water content NDWI is still an image signal, so x can be set to represent any pixel point on the vegetation index NDVI, and y can be set to represent any pixel point on the vegetation water content NDWI, and the vegetation degree analysis formula used can be:

[0057]

[0058] Similarly, since the image signals of the vegetation index NDVI and the vegetation water content NDWI have the same size, they can be assumed to have n pixels each in formula (3), and r in formula (3) represents the vegetation degree.

[0059] It can be seen from formula (3) that after performing relevant summation, product, square, subtraction, multiplication, square root and division operations on each pixel point x of the vegetation index NDVI and each pixel point y of the vegetation water content NDWI, the size of the vegetation degree r obtained can be, for example, a value not exceeding 1 (i.e., between -1 and 1). According to the application of the vegetation degree analysis formula in the current technology, when the vegetation degree r is closer to 1, it means that the correlation between the vegetation index NDVI and the vegetation water content NDWI is greater; conversely, when the vegetation degree r is farther away from 1, it means that the correlation between the vegetation index NDVI and the vegetation water content NDWI is smaller.

[0060] Therefore, when the vegetation degree r is within a specified range from the value 1, it means that the vegetation index NDVI and the vegetation water content NDWI are positively correlated; that is, the food status information represented by the vegetation index NDVI or the food status information represented by the vegetation water content NDWI can be adopted. Similarly, the specified range can be set according to the application situation or actual needs, that is, the degree to which the vegetation degree r is close to 1.

[0061] However, when the vegetation degree r exceeds the specified range from the value 1, although it means that the vegetation index NDVI and the vegetation water content NDWI are not closely related, it does not mean that the results of the vegetation index NDVI or the vegetation water content NDWI are incorrect. This is because the vegetation index formula is more suitable for identifying vegetables, while the vegetation water content formula is more suitable for identifying fruits, and there are many types of vegetables and fruits. The state of some vegetables or fruits may not be applicable to both the vegetation index formula and the vegetation water content formula.

[0062] As mentioned above, for this situation with less correlation, it can be designed to give priority to the identification result of the vegetation index formula, or give priority to the identification result of the vegetation water content formula, or return to the process after the name or type of the food is identified. Since not all fruits and vegetables have chlorophyll, which exists in plant leaves, other red, yellow, and purple fruits and vegetables are mainly composed of pigments such as carotenoids and anthocyanins, and contain less chlorophyll, so it is necessary to consider using a suitable formula for state identification. For example, red, yellow, and purple fruits and vegetables can be identified according to the wavelength characteristics of the pigment of the variety, that is, mainly carotenoids or anthocyanins and containing a small amount of chlorophyll, using multiple spectra from blue light to red light, near-infrared light, and short-wave infrared light to identify the texture of fruits and vegetables by image gradient analysis, or by image contrast analysis to identify the brightness of fruits and vegetables, so as to identify their freshness or state.

[0063] In addition, when fresh fruits and vegetables are placed in the refrigerator, the temperature they are exposed to is lowered, so the rate of chlorophyll synthesis in the leaf tissue will begin to slow down. When the number of days of cold storage increases, the water content in the leaf tissue begins to decrease, and decomposition also begins to occur at low temperatures, so that the synthesis rate cannot be replenished in time, causing the chlorophyll pigment content to gradually decrease. However, carotene is more stable than chlorophyll. Even if the chlorophyll disappears, carotene can still exist in the leaves. The lutein and carotene in the leaves will gradually dominate under cold storage, so that the blue light and blue-green light bands will be absorbed, so that the spectrum of 570 to 680 nanometers (nm) can be used for identification. Therefore, under the concept of the present invention, the sensing of multiple bands can be used by image analysis technology of fruit and vegetable texture and brightness to provide the vegetation index formula or the vegetation water content formula for more flexible use.

[0064] In the preferred embodiment, although the above-mentioned formula (1), formula (2) and formula (3) are used to represent the vegetation index formula, the vegetation moisture content formula and the vegetation degree analysis formula respectively, it can be understood that under the concept of the present invention, other vegetation index formulas, vegetation moisture content formulas and vegetation degree analysis formulas with similar design purposes but different contents can also be used in other embodiments, and they can all achieve similar or the same food state identification effect.

[0065] On the other hand, although the food state identification and display method of the present invention is mainly used to identify the state of vegetables and fruits, the structure and method of the present invention can also be applied to the identification of meat, fish or other types of food. In detail, the image can also be identified by the image recognition program to identify the type of food. If it is meat, fish or other types of food, the visible light image signal can be compared with a food database.

[0066] For example, if most of the image of the meat is bright red, the corresponding food status information is set to have content representing that the food status is fresh; on the other hand, if part of the image of the meat is black, the corresponding food status information is set to have content representing that the food status is not fresh.

[0067] The above preferred embodiment is illustrated by the food storage environment 11 in the refrigerator 10, but the concept of the present invention is not limited thereto. For example, in other embodiments, the food storage environment can be designed to be a food display area in a supermarket, a traditional market, a store or a store, and the user device is a mobile electronic device, such as a smart phone, a tablet computer or a wearable electronic device, and the camera and light source module, the processing module and the display interface are arranged on the user device. Secondly, the food status identification and display function can be provided to the processing module of the user device for access and execution in the form of relevant firmware or program code.

[0068] In other words, this implementation method allows the user to take the mobile electronic device to the food display area of ​​a supermarket, traditional market, store or shop, and use the camera and light source module on the mobile electronic device to take photos of the displayed food. Then the processing module will receive, process and analyze the photographic results, and then display the corresponding food status information generated on the display interface (i.e., screen) for the user to watch. In this way, the user can also use this function to understand the freshness of the relevant food before purchasing it, and then decide whether to buy it.

[0069] As mentioned above, since modern people seldom cook by themselves or lack experience in purchasing ingredients in their busy business life, when they need to select and purchase ingredients by themselves, the food status recognition and display architecture and the food status recognition and display method applied thereto of the present invention can provide them with good help.

[0070] Alternatively, in other embodiments, the display interface may also be a screen element configured for the refrigerator, that is, the user can directly stand in front of the refrigerator and look at the screen to understand the status or freshness of the food stored therein without the need for additional user devices or mobile electronic devices.

[0071] In summary, the food state identification and display architecture and the food state identification and display method applied thereto proposed by the present invention have the following improvements compared to the prior art: First, the camera and light source module of the present invention can take photos with a larger viewing angle or a larger photographing range, so only a single lens module can be used for setting, and multiple spectral bands can be sensed, effectively saving the setting cost of the overall architecture. Second, the present invention uses a vegetation index formula, a vegetation moisture content formula, and a vegetation degree analysis formula to analyze the food photography results. This method has a good and correct effect on the freshness, state, or authenticity of vegetables and fruits. Third, in addition to being applied to smart refrigerators, the architecture of the present invention can also be applied to supermarkets, traditional markets, stores, or shops with food display areas, so that users can have relevant information for reference when selecting and purchasing food.

[0072] Therefore, the present invention can effectively solve the related problems raised in the prior art and successfully achieve the main purpose of the development of this case.

[0073] Although the present invention has been disclosed as above by way of embodiments, it is not intended to limit the present invention. A person skilled in the art of the present invention may make various modifications and alterations without departing from the spirit and scope of the present invention. Therefore, the protection scope of the present invention shall be determined by the following claims.

Claims

1. A food status identification and display architecture, comprising: a camera and light source module, which is used to face a food storage environment and photograph at least one food in the food storage environment using a visible light band, a near infrared light band, and a short-wave infrared light band to generate a food photography result; a processing module, for receiving the food photography result, and processing and analyzing the food photography result by means of an image recognition program, a vegetation index formula, a vegetation moisture content formula and a vegetation degree analysis formula, so as to generate corresponding at least one food status information and transmit it; and A display interface is used to receive and display the corresponding at least one food status information for viewing.

2. The food status identification and display architecture as described in claim 1, wherein the architecture further includes a refrigerator, the food storage environment is formed in the refrigerator, the camera and light source module is arranged in the refrigerator in a manner of facing the food storage environment, and the processing module is arranged in the refrigerator in a manner of being signal-connected to the camera and light source module.

3. The food status identification and display architecture as described in claim 2, wherein the architecture further includes a user device, the display interface is set on the user device, and the refrigerator has a network transmission module connected to the processing module by signal, and the network module is used to receive the corresponding at least one food status information and transmit it to the user device via a wired or wireless network.

4. The food state recognition and display architecture as claimed in claim 1, wherein the camera and light source module comprises a wide-angle lens module or a fisheye lens module.

5. The food state recognition and display architecture as described in claim 1, wherein the camera and light source module has a visible light source, a near infrared light source, a short wave infrared light source, a visible light sensing chip, a near infrared light sensing chip and a short wave infrared light sensing chip, and can respectively sense with the visible light band, the near infrared light band and the short wave infrared light band to generate the food photography result.

6. The food state recognition and display architecture as claimed in claim 1, wherein the camera and light source module has a multi-band sensing chip integrating sensing functions of the visible light band, the near infrared light band and the short-wave infrared light band.

7. The food state recognition and display architecture as described in claim 1, wherein the food photography result includes a visible light image signal, and the image recognition program loads the visible light image signal, and performs image correction, captures and classifies the visible light image signal into one or more regions of interest in a predetermined mode, and determines the corresponding food name of its image content.

8. The food state identification and display architecture as described in claim 1, wherein the food photography result includes a near-infrared light image signal and a red light image signal, and the vegetation index formula is the result of subtracting the red light image signal from the near-infrared light image signal and dividing it by the value of the near-infrared light image signal plus the red light image signal, which is defined as a vegetation index.

9. The food status identification and display architecture as described in claim 8, wherein when the vegetation index is within a specified range from the value 1, the corresponding at least one food status information is set to have content representing that the food status is fresh, and when the vegetation index exceeds the specified range from the value 1, the corresponding at least one food status information is set to have content representing that the food status is not fresh.

10. The food state recognition and display architecture as described in claim 1, wherein the food photography result includes a near-infrared light image signal and a short-wave infrared light image signal, and the plant moisture content formula is the result of subtracting the short-wave infrared light image signal from the near-infrared light image signal and dividing it by the value of the near-infrared light image signal plus the short-wave infrared light image signal, which is defined as a plant moisture content.

11. The food status identification and display architecture as described in claim 10, wherein when the plant moisture content is within a specified range from the numerical value 1, the corresponding at least one food status information is set to have content representing that the food status is fresh, and when the plant moisture content is beyond the specified range from the numerical value 1, the corresponding at least one food status information is set to have content representing that the food status is not fresh.

12. The food state identification and display architecture as claimed in claim 8 or 10, wherein the vegetation degree analysis formula uses the vegetation index and the vegetation water content to perform a correlation analysis, and the result is defined as a vegetation degree.

13. The food state identification and display architecture as claimed in claim 12, wherein when the vegetation level is within a specified range from a value of 1, it represents that the vegetation index and the vegetation water content are positively correlated.

14. The food state identification and display architecture as described in claim 1, wherein the architecture further includes a user device, and the camera and light source module, the processing module and the display interface are arranged on the user device, and the food storage environment is a food display area.

15. A method for identifying and displaying food status, applied to a food status identification and display architecture, the architecture comprising a camera and light source module, a processing module and a display interface, the method comprising the following steps: Directing the camera and light source module toward a food storage environment and photographing at least one food in the food storage environment using a visible light band, a near infrared light band, and a short-wave infrared light band to generate a food photography result; The processing module receives the food photography result, and processes and analyzes the food photography result by means of an image recognition program, a vegetation index formula, a vegetation moisture content formula, and a vegetation degree analysis formula, thereby generating at least one corresponding food status information and transmitting it; and The display interface receives and displays the corresponding at least one food status information for viewing.

Images