Camera interlocked illumination control system

Abstract

To bring illumination light into chromaticity suitable for a target without exchanging an illumination device.SOLUTION: A camera interlocked illumination control system comprises a camera, a device including an image recognition function, an illumination control device, and a target illumination device. The target illumination device illuminates a target region, where a target may be present, with first illumination light. The camera photographs the target region and acquires an image including a background and the target. The device including the image recognition function extracts a target image region, which is a region of the target in the image, and recognizes a kind of the target or a color of the target. The illumination control device sets chromaticity of second illumination light in accordance with the kind of the target or the color of the target. The camera photographs the target region again and acquires the image including the background and the target again. Even in a case where a ratio of an area of the target image region with respect to an area of the background in the image acquired again is decreased less than a ratio of the area of the target image region with respect to the area of the background in the image acquired before, the target illumination device irradiates the target region with the same second illumination light.SELECTED DRAWING: Figure 1

Description

[Technical field]

[0001] The present invention relates to a camera-linked lighting control system equipped with a camera and a lighting device. [Background technology]

[0002] A system has been proposed that links lighting devices and cameras to control the lighting devices based on image information captured by the cameras. Patent Document 1 proposes a system that uses a camera and an image processing unit as a person position detection means to perform lighting control so as to turn on a lighting device corresponding to the position of a person.

[0003] Patent Document 2 describes an illumination device that makes meat look more vivid.

[0004] Patent Document 3 describes an illumination system in which a light-emitting unit is driven based on light-emitting mode data associated with the type of food that is the illumination target.

[0005] Patent Document 4 describes an illumination device that can irradiate the optimal light for each food ingredient by using a first light source of warm color in which the spectral components of blue light, red light, and green light are mixed in a predetermined ratio, a second light source of high color temperature in which the spectral components of blue light, red light, and green light are mixed in a ratio different from that of the first light source, and a third light source that has only a blue light spectral component. [Prior art documents] [Patent documents]

[0006] [Patent Document 1] JP 2014-007123 A [Patent Document 2] JP 2013-127855 A [Patent Document 3] JP 2013-077387 A [Patent Document 4] Patent No. 5507148 Summary of the Invention [Problem to be solved by the invention]

[0007] For example, in supermarkets, it is desirable to provide lighting that is most suitable for the products on display, and lighting devices that optimize the color of the lighting light according to the type of product are commercially available. However, for example, in the fruit section, it is necessary to stop selling spring fruits and display summer fruits, or to expand the display area depending on sales. In such cases, there is a problem that the lighting devices must also be replaced.

[0008] SUMMARY OF THE PRESENT DISCLOSURE An object of the present invention is to provide a camera-linked lighting control system that can adjust the chromaticity of illumination light to suit an object without the need to change lighting devices depending on the object. [Means for solving the problem]

[0009] The present invention provides a camera-linked lighting control system including a camera, a device having an image recognition function, a lighting control device, and an object lighting device, The object illumination device illuminates an object area in which an object may exist with a first illumination light; The camera photographs the target area to obtain an image including a background and the target object; The device having the image recognition function extracts an object image area that is an area of ​​the object from the image, and recognizes the type or color of the object from the object image area; the lighting control device sets a chromaticity of the second illumination light in accordance with a type or a color of the object; The camera photographs the target area again to obtain an image including the background and the target again; The object lighting device is a camera-linked lighting control system that irradiates the object area with the same second lighting light even if the ratio of the area of ​​the object image area to the area of ​​the background in the re-acquired image becomes smaller than the ratio of the area of ​​the object image area to the background in the previously acquired image.

[0010] In the present invention, the device having the image recognition function may further calculate an average chromaticity of the object image region from the object image region, and recognize the average chromaticity as the color of the object.

[0011] In the present invention, the average chromaticity may be calculated by dividing the object image region into color regions of a plurality of representative colors and calculating a weighted average of the chromaticity and area of ​​each color region.

[0012] In the present invention, the device having the image recognition function may further refer to learning data for image recognition to identify the object image area in the image and recognize the type of the object.

[0013] In the present invention, the first illumination light may further have chromaticity on the blackbody radiation locus. Effect of the Invention

[0014] In the present invention, the illumination light of the object illumination device can be controlled to a chromaticity suitable for the color tone of the object, thereby making it possible to make the object appear in a desired color tone. [Brief description of the drawings]

[0015] [Figure 1] FIG. 1 is a configuration diagram of a camera-linked lighting control system according to a first embodiment. [Diagram 2] Flowchart of image recognition and lighting by the camera-linked lighting control system of embodiment 1 [Diagram 3] Image captured for area setting in the camera-linked lighting control system of embodiment 1 [Figure 4] An image showing an object and a background in the camera-linked lighting control system of the first embodiment [Diagram 5] FIG. 1 is a chromaticity diagram for explaining chromaticity control in the camera-linked lighting control system according to the first embodiment. [Figure 6] A chromaticity diagram explaining the chromaticities of three colors: red, yellow-white, and blue-white. [Figure 7] Configuration diagram of a camera-linked lighting control system according to the second embodiment [Figure 8] Graph showing an example of scheduled operation of general lighting devices [Figure 9] Chromaticity diagram for explaining chromaticity control of general lighting device and object lighting device [Figure 10] FIG. 1 is an explanatory diagram of a method of using a two-dimensional barcode to indicate the lighting conditions for illuminating an object or an area of ​​interest in the first embodiment. [Figure 11] FIG. 1 is an illustration of a method of using an LED signal transmitter to indicate lighting conditions for illuminating an object or area of ​​interest in accordance with embodiment 1. [Figure 12] FIG. 11 is an explanatory diagram showing the relationship between food and the color temperature of illumination that makes the food taste delicious in the third embodiment. [Figure 13] Configuration diagram of a camera-linked lighting system according to the fourth embodiment [Figure 14] Inside the lamp body of the object lighting device of embodiment 4 [Figure 15] FIG. 11 is a plan view of a light source used in the object illumination device of the fourth embodiment; [Figure 16] Chromaticity diagram of three-color LEDs used in the object illumination device of embodiment 4 [Figure 17] Spectral diagram of LEDs (D, F) used in the object illumination device of embodiment 4 [Figure 18] Spectral diagram of LEDs (D, E) used in the object illumination device of embodiment 4 [Figure 19] Chromaticity diagram (full chromaticity range) of three-color LEDs used in the object illumination device of embodiment 4 [Figure 20] Schematic diagram to explain color unevenness [Figure 21] FIG. 13 is a diagram showing the configuration of an object lighting device used in the camera-linked lighting system of the fifth embodiment. [Figure 22] FIG. 13 is an exploded perspective view of a lamp body of the object illumination device according to the fifth embodiment. [Diagram 23] Chromaticity diagram of four-color LEDs used in the object illumination device of embodiment 5 [Figure 24] Synthetic spectrum obtained in the object illumination device of embodiment 5 [Diagram 25] Configuration diagram of a camera-linked lighting control system according to the sixth embodiment [Figure 26] Flowchart of image recognition and lighting by the camera-linked lighting control system of embodiment 6 [Figure 27] FIG. 13 is an explanatory diagram of image segmentation in the camera-linked lighting control system of the sixth embodiment. [Figure 28] Configuration diagram of a camera-linked lighting control system according to the seventh embodiment [Figure 29] FIG. 13 is an explanatory diagram of image segmentation in the camera-linked lighting control system of the seventh embodiment. [Diagram 30] Flowchart of image recognition and lighting by the camera-linked lighting control system of embodiment 7 [Diagram 31] FIG. 13 is an explanatory diagram of a photograph of a refrigerated case with a meat tray and its image segmentation in the camera-linked lighting control system of the seventh embodiment. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0016] <Embodiment 1> <Application> The configuration of a camera-linked lighting control system 100 according to the first embodiment is shown in Fig. 1. This is a camera-linked lighting control system that photographs an object with a camera and illuminates the object with light of a color tone suited to its color.

[0017] <Configuration> The camera-linked lighting control system 100 includes a camera 110 installed on a ceiling 190, a camera and lighting control device 130, object lighting devices 160A and 160B, a gateway 155, a camera control device monitor 132 located at a person's hand, a second lighting control device 150, and the like.

[0018] <Object Illumination Device> The single or multiple object lighting devices 160 (the number of devices may be any number, but in the case of two, for example, they are referred to as object lighting devices 160A and 160B) are, for example, spotlights, and respectively irradiate objects 180A and 180B (referred to as object 180 when A and B are not distinguished) in object regions 183A and 183B (referred to as object 183 when A and B are not distinguished) with illumination light 162A and 162B (referred to as illumination light 162 when A and B are not distinguished). The object lighting device 160 can change the chromaticity of the illumination light, and it is preferable that it can change the color deviation Duv (described later), which is a factor other than color temperature. Such a change in the chromaticity of the illumination light is performed using the second illumination control device 150 or the camera and illumination control device 130.

[0019] <Object> Objects 180A and 180B are placed on backgrounds 182A and 182B, respectively (when no distinction is made between A and B, they are referred to as background 182).

[0020] <Lighting control device> The second lighting control device 150 is a tablet-type terminal device that includes a touch panel display that serves as both an input unit and a display unit, and also includes a control unit, a storage unit, and a wireless communication unit. In the second lighting control device 150, the brightness (total luminous flux) and color of the object lighting device 160 and the like can be controlled by operating lighting control software. The lighting control software can also perform schedule control that changes the control content depending on the time. The second lighting control device 150 may be a computer, a smartphone, or the like.

[0021] <Gateway> It is possible for the second lighting control device 150 to send a lighting control signal directly (without going through the gateway 155) to the object lighting device 160, but particularly when the second lighting control device 150 is a portable device such as a tablet, it is also possible to transmit, for example, schedule control information via wireless communication 152 to the gateway 155 installed in a fixed location, which the gateway 155 stores, and at a predetermined time transmits a lighting control signal to the object lighting device 160 via wireless communication 154. This is because there are cases in which normal wireless communication cannot be performed from the portable second lighting control device 150.

[0022] <Camera and camera / lighting control device> The camera 110 is, for example, a camera with a fisheye lens, and captures an image 113 within a field of view 112 and transmits it to a camera and lighting control device 130 .

[0023] The camera and lighting control device 130 is a device having camera control functions and lighting control functions, and also has an image recognition function. The functions are realized by a computer, which is hardware, and software. As an output device, for example, a camera control device monitor 132 is provided, which displays the image 113 and the control contents. The camera and lighting control device 130 is connected to a gateway 155 via a communication line 157.

[0024] The camera / lighting control device 130 may not be equipped with the camera control device monitor 132 and may be operated by communicating with a separate PC or tablet.

[0025] <Lighting control configuration> The object lighting device 160 performs an operation preset by the second lighting control device 150, which is composed of a tablet or the like, or the camera and lighting control device 130. The operation is stored in, for example, the gateway 155, which is a repeater. When an instruction is received from the camera and lighting control device 130 or the second lighting control device 150, the gateway 155 transmits an operation preset for the instruction to the object lighting device 160, and the object lighting device 160 operates according to the instruction of the second lighting control device 150 and the camera and lighting control device 130. Note that communication between these devices is performed through a communication line 117 between the camera 110 and the camera and lighting control device 130, a communication line 157 between the camera and lighting control device 130 and the gateway 155, a wireless communication 152 between the second lighting control device 150 and the gateway 155, and a wireless communication 154 between the gateway 155 and the object lighting device 160, but the wired communication may be wireless communication, and the wireless communication may be wired communication. In addition, communication using infrared rays or visible light may be performed as the communication.

[0026] <Image Recognition and Lighting Flowchart> A flowchart of image recognition and lighting by the camera-linked lighting control system 100 is shown in Figure 2. S1 to S5 are initial settings, and are performed when the target area is changed due to rearrangements of the room, etc. S6 and onwards are performed for each target area (although the camera 110 captures an image of the entire area). The loop from S11 to S6, or S9 to S6, can be performed manually when the target object is changed, or in the case of a store, it can be performed once a day before opening, or at regular time intervals, etc. as appropriate.

[0027] In "S1. Initial lighting", the object lighting devices 160A and 160B are turned on.

[0028] In "S2. Acquiring initial image", an image 113 is captured by the camera 110, and the image data is input to the camera and lighting control device 130.

[0029] In "S3. Area setting", the image 113 captured for area setting, as shown in Fig. 3, is displayed on the camera control device monitor 132. Although the image 113 has distortion specific to fisheye lens images, the operator manually specifies the target areas 183A and 183B, which are as small as possible and have shapes such as a rectangle or a circle, that contain the objects 180A and 180B, and stores them in the camera and lighting control device 130. The coordinates of the target areas set here are also used to cut out the target areas in images captured later.

[0030] In addition to manually setting the target area, it can also be set automatically. Figure 4 shows an image containing an object 180 and a background 182. The image recognition function can recognize the area containing the background 182 and set it as the target area 183. In this case, if a "distinctive background" that is easy for the image recognition function to recognize is used as the background pattern, there is an advantage that even a relatively low-cost device with image recognition function can recognize the background. Here, a grid pattern of white (W), light gray (WD), and gray (D) is used as the "distinctive background." In this case, the image recognition function can recognize corners, etc., indicated by CN, and recognize them as "background" from a regular pattern.

[0031] In "S4. Correspondence between areas and lighting devices", the camera control device monitor 132 associates the target area 183A with the object lighting device 160A, and the target area 183B with the object lighting device 160B (similarly if there are other object lighting devices and target areas).

[0032] This enables the camera and lighting control device 130 to control the object lighting devices 160A and 160B via the gateway 155.

[0033] In "S5. Acquiring background image", an image of the entire area is captured excluding the object. This makes it possible to obtain images of the object areas 183A and 183B without the object.

[0034] "S6. Reducing the color deviation of the illumination light in the target area to zero" is a desirable step for accurately recognizing the chromaticity of the target in "S10. Recognizing the target object", but it is not essential. "Reducing the color deviation to zero" means using illumination light close to the "black body radiation locus BBL" described later.

[0035] In "S7. Acquire target image", the camera 110 acquires an image 113 of the target object placed on the surface.

[0036] In "S8. Cut out area of ​​target image", the camera and lighting control device 130 cuts out the image of the target area 183A and 183B whose area was set in S3.

[0037] In "S9. Comparison of background image and target image of target area", the background image and target image acquired by the camera and lighting control device 130 in S5 are compared for the target area. Here, the "target image" is as shown in FIG. 4.

[0038] If the object 180 is placed in the target image, it is determined to be "different" from the background image, and the process proceeds to the next step (recognition of the object).

[0039] On the other hand, if the object 180 is not placed in the target image, it will be "same", so the process returns to S6 and the color deviation of the illumination light in the target area is set to zero. Since there is no object, there is no need to emphasize the color, and it is desirable to illuminate with a natural color.

[0040] <Object Recognition> In "S10. Recognizing Object", the image recognition function recognizes the object 180 in the object area 183.

[0041] Here, the "image recognition function" is realized as a function executed by software in the camera and lighting control device 130, and at least a part of the camera and lighting control device 130 becomes the "image recognition function". On the other hand, the "image recognition function" may be realized by being built into the camera 110. Also, the "image recognition function" may be realized in an external server or external PC connected to the camera-linked lighting control system 100.

[0042] There are various methods for recognizing objects. One is a method in which the image recognition function does not recognize the shape, but recognizes the color histogram for each pixel, extracts colors other than the color components in the background image, and identifies the color of the object 180. Here, it is also possible to simply detect the color of the object without going so far as to recognize what the object is, and with this, it is possible to perform lighting control such as "if the object is red, make the color deviation Duv of the chromaticity of the illumination light on the negative side" and "if the object is green or yellow, make the color deviation Duv of the chromaticity of the illumination light on the positive side," as described below.

[0043] If the color of the object is similar, the size and shape of the object can be identified, and the object and its color can be recognized based on that. In other words, a small "cherry" (e.g., 1 cm diameter) and a large "apple" (e.g., about 7 cm diameter) can be recognized based on their size. Also, a "cherry" and a "strawberry" (e.g., 3 cm diameter) can be recognized based on their size.

[0044] In addition, when the color of the object is similar, the object can be recognized by its shape, such as a "round lemon" or a "long, thin banana."

[0045] In other words, it is desirable to recognize an object using at least one of its color distribution, size, and shape.

[0046] Furthermore, a technique called deep learning may be used to recognize objects. By having AI (Artificial Intelligence) learn the relationship between many images and objects in advance, the AI ​​as an image recognition function can recognize objects.

[0047] On the other hand, as a method of recognizing the object 180, instead of the object 180 itself, a display such as a sign with the word "apple" or a barcode or two-dimensional barcode that displays the object 180 may be recognized.

[0048] Fig. 10 is an explanatory diagram of a method for identifying the lighting conditions for illuminating an object or a target area by using a two-dimensional barcode. As shown in Fig. 10, a QR code (registered trademark) 184, which is a two-dimensional barcode that covers a wide area within a target area 183, is prepared, and this QR code 184 is photographed by camera 110. The area of ​​QR code 184 is made large because camera 110 has a wide angle and the target area is captured small, but QR code 184 may be of any size as long as it can be identified by camera 110.

[0049] When QR code 184 indicates the name of an object (for example, "marbled beef"), camera and lighting control device 130 controls the chromaticity of object lighting device 160 to the chromaticity corresponding to the object name. At this time, a table showing the correspondence between object names and lighting conditions (chromaticity, color temperature, color deviation, total luminous flux) is stored in advance in camera and lighting control device 130 or in a storage device accessible by camera and lighting control device 130. When QR code 184 indicates the lighting conditions themselves, camera and lighting control device 130 controls the lighting conditions such as the chromaticity of object lighting device 160 under the lighting conditions indicated by QR code 184 read by camera 110.

[0050] Instead of QR code 184, a single or multiple patterns or marks such as circles, squares, triangles, crosses, etc. corresponding to the object or lighting conditions (chromaticity, color temperature, color deviation, total luminous flux) may be provided in target area 183, and specifically, a covering such as a tablecloth with a pattern or mark may be placed.

[0051] Also, an LED signal transmitter 185 that indicates the lighting conditions for illuminating the object or the object area may be installed in the object area. Fig. 11 is an explanatory diagram of a method using an LED signal transmitter. The LED signal transmitter 185 blinks visible light or infrared light corresponding to, for example, the object name or the lighting conditions, and the camera and lighting control device 130 analyzes the blinking through the camera 110 and controls the lighting conditions of the object lighting device 160.

[0052] The LED signal transmitter 185 may control the lighting conditions by the number of LEDs that light up within the target area, for example, by including multiple LEDs and indicating "for vegetables" when one LED lights up or flashes, or "for meat" when two LEDs light up or flash.

[0053] The above-mentioned notices, bar codes, two-dimensional bar codes, patterns and marks, LED signal transmitters, etc., which indicate objects, are collectively referred to as object identification members.

[0054] The camera-linked lighting control system 100 may be constantly operating during the store's business hours, for example, with the camera 110 automatically photographing the object identification member, and the camera-linked lighting control system 100 automatically controlling the lighting conditions. For example, the store manager may train a new sales clerk to replace the object identification member and display a different product when a product in the target area is sold out, and the camera-linked lighting control system 100 automatically illuminates the different product under lighting conditions suitable for the new product without the new sales clerk having to manually give instructions to change the lighting conditions.

[0055] <Lighting control according to the color of the object> In "S11. Illuminate the target area with illumination light according to the recognition result", illumination control is performed according to the color of the target. If there are multiple target areas, illumination control is performed individually for each object illumination device corresponding to each target area, and the target areas are illuminated.

[0056] 5 is a chromaticity diagram for explaining chromaticity control in the camera-linked lighting control system 100, showing chromaticity (x, y) in the CIE 1931 chromaticity coordinates. The x-axis represents the x chromaticity coordinates, the y-axis represents the y chromaticity coordinates, BBL represents the blackbody radiation locus, T CCT indicates correlated color temperature, and Duv indicates color deviation (1000 times duv).

[0057] As described in "S6. Setting the color deviation of the illumination light in the target area to zero," in order to accurately capture the color of the object 180 when recognizing the object 180, it is preferable that the emission color of the object illumination device 160 is a color close to the blackbody radiation locus BBL, and one example is light with a color temperature of 4000K and color deviation Duv=0 as shown at point Z. In other words, if light of a color suited to a different object was irradiated before recognizing the object 180, it is preferable (but not essential) to "reset" it to a color along the blackbody radiation locus BBL before recognizing the color of the object.

[0058] As described in "S5. Acquiring a Background Image", before recognizing the object 180, only the background 182 is illuminated with light from point Z without placing the object 180, and the image is compared with the image of the object 180. This can improve color recognition of the object 180. In this case, it is preferable that the background 182 is an achromatic color such as gray.

[0059] Returning to the discussion of "S11. Illuminate the target area with lighting according to the recognition results," if the recognized object is "bread" or "sweets," the chromaticity coordinates of the lighting are set to point N1 or N2. If the object is "beef," the chromaticity of the lighting is set to point M2. If the object is pork, the chromaticity of the lighting is set to point M1. If the object is blue fish (sardines, mackerel, etc.), the chromaticity of the lighting is set to point F. If the object is leafy vegetables, the chromaticity of the lighting is set to point G. If the object is a yellow lemon, the chromaticity of the lighting is set to point L.

[0060] These chromaticities of the illumination light are examples, and other chromaticities of the illumination light may be used depending on the type and condition of the food. For example, even for red foods, it is preferable to change the chromaticity of the illumination light finely depending on whether the food is apple, strawberry, beef, salmon roe, wine, etc. Even if the object is green, it is preferable to change the chromaticity of the illumination light finely depending on whether the food is melon or leafy vegetables. Even if the object is yellow, it is preferable to change the chromaticity of the illumination light finely depending on whether the food is lemon, banana, or egg dish. In addition, since the chromaticity of the illumination light is influenced by people's preferences, it is preferable that it can be adjusted by users such as supermarket sales staff. In this case, it is fine to adjust it depending on sales, but it may also be adjusted taking into consideration the age, sex, eye color (race), and income level of main customers.

[0061] This camera-linked lighting control system can be used not only for food but also for clothing, car bodies, stationery, and other products where color is important, to illuminate with a chromaticity that brings out the appeal of the product, leading to increased sales.

[0062] In "S9. Comparison of background image of target area with target image", if camera 110 determines that target object 180 does not exist, it is preferable to make the total luminous flux of the illumination light from target object illumination device 160 smaller than the total luminous flux when target object 180 exists (for example, 1 / 10), or to turn it off. The purpose of this is not only to reduce power consumption, but also, in the case of a product, to visually indicate that the product is sold out.

[0063] Whether or not the object 180 exists is determined, for example, as follows. First, a background image in which no object exists is captured in advance, and the object area is cut out. Then, the feature amounts / vectors are calculated in the target region, and the calculation results are stored as A. Then, for example, images of the target area are captured at regular time intervals during business hours, and the target area is cut out. Then, the feature amounts / vectors are calculated in the target region, and the calculation results are stored as B. B and A are compared to determine whether the difference is greater than a preset threshold. If the difference between B and A is not greater than the threshold, it is determined that B and A are similar, i.e., there is no target object.

[0064] AKAZE (Accelerated KAZE) feature detection can be used as a method for calculating feature quantities / vectors. This is a method of matching by converting the input image to monochrome (an image containing only the V values ​​(Hue, Saturation, and Value) of HSV). Using an image containing only V has the effect of reducing the amount of processing and absorbing color changes in the background image caused by the color of the lighting.

[0065] Since AKAZE feature detection cannot accurately calculate similarity for images with no pattern or with rough edges, the following image correlation method may be used.

[0066] Calculate the average values ​​Aave and Bave of the pixel information of A and B above. This is used to correct the brightness of the background image and the target image. Next, the average value of B*Ave / Bave-A = E is taken as the similarity. In terms of meaning, it is the sum of the differences of each pixel after luminance correction. The presence or absence of an object is judged as follows: if E<threshold (images are similar), it is judged that there is no object; if E≧threshold (images are different), it is judged that there is an object.

[0067] Although these algorithms have been described as an example of determining whether an object is present or not, they can also be used to determine what the object is.

[0068] In "S10. Recognizing objects", the K-means method can be used to extract representative colors from the image data of the object and recognize what the object is based on the representative colors. This is a method in which each pixel of an image plotted in a color space such as RGB or HSV is classified into N color regions (N is 2 or more), and the average value of the region with the largest number of pixels in the classified color space is used as the representative color.

[0069] In such cases, the representative color may be the color of the background, tray, plate, label, or other object, but it is desirable to carry out processing to remove such representative colors from the candidates for the object's color.

[0070] As a result, if the object is beef, for example, it is possible to determine that the representative color of the object is closer to the representative color of beef than the representative color of an apple that has been acquired in advance, and identify the object.

[0071] As described above, it is desirable to set the chromaticity of the illumination light to match the color of the object, but it is particularly preferable to control it so that "if the object is red, the chromaticity deviation Duv of the illumination light is set to the negative side," and "if the object is green or yellow, the chromaticity deviation Duv of the illumination light is set to the positive side." In other words, it is preferable to "change the chromaticity of the illumination light in the same direction as the chromaticity deviation of the object color according to the chromaticity deviation, which is the difference between the chromaticity coordinates of the object and the chromaticity coordinates on the blackbody radiation locus that are close to those chromaticity coordinates." Such chromaticity of the illumination light emphasizes the color of the object, bringing out the deliciousness of food and the vividness of other objects, which can lead to increased sales of the product.

[0072] It is advisable to use the chromaticity of the illumination light that is slightly closer to the chromaticity on the blackbody radiation locus than to the color of the object itself. For example, the chromaticity coordinates of the above-mentioned "leafy vegetables" are (0.35, 0.50), which is green, but the chromaticity of the illumination light for G is (0.37, 0.40), which is closer to the blackbody radiation locus. In this way, a person looking at the object will perceive the color of the object as vivid when illuminated with normal white light. If the object is illuminated with the color of the object, even a white tray with the object on it will look like the color of the object, resulting in very unnatural coloring.

[0073] In S11, not only the chromaticity of the object lighting device 160 is adjusted but also the total luminous flux may be controlled (dimmed). The camera 110 can detect whether the object 180 is bright or dark in the image of the object area 183, and can dim the object lighting device 160 that illuminates the object area so that the object 180 has an appropriate brightness.

[0074] <Light source for lighting equipment> The light source of the object illuminator 160 is one that can vary the color deviation Duv. Normal illuminators include fixed-color illuminators that use a single-color light source and color-adjustable illuminators that use two-color light sources and have variable color temperature, but neither of these has the function of varying the color deviation Duv. A suitable object illuminator 160 has light sources of three or more colors, for example, one that uses the three primary colors R, G, and B (red, green, and blue). Also suitable is an illuminator that uses the three colors R, Yw, and Bw (red, yellow-white, and bluish-white) described below.

[0075] Figure 6 shows a chromaticity diagram explaining the chromaticity of the three colors R·Yw·Bw (red, yellowish white, and bluish white). An R-LED, which is a light-emitting element for the primary color red (R), a Bw-LED, which is a light-emitting element for the non-primary color bluish white (Bw), and a Yw-LED, which is a light-emitting element for the non-primary color yellowish white (Yw), are used. For red (R), the chromaticity is in the range enclosed by the chromaticity boundary line E, i.e., (0.66,0.23), (0.423,0.355), and (0.5,0.5) in the CIE1931 chromaticity coordinates shown in Figure 6. For bluish white (Bw), the chromaticity is in the range enclosed by the chromaticity boundary line E, i.e., (0.66,0.23), (0.423,0.355), and (0.5,0.5). For red (R), the chromaticity is in the range enclosed by the chromaticity boundary line E, i.e., (0.66,0.23), (0.423,0.355), and (0.5,0.5). For blue ... In terms of coordinates, the color of chromaticity in the range surrounded by (0.336, 0.24), (0.352, 0.44), (0.15, 0.2), and (0.2, 0.1), and yellowish white (Yw), is preferably a color of chromaticity in the range surrounded by (0.5, 0.5), (0.423, 0.355), (0.342, 0.312), (0.352, 0.44), (0.37, 0.63) in the CIE1931 chromaticity coordinates and the chromaticity boundary line E. This makes it possible to widely reproduce colors along the blackbody radiation locus, such as 1800K to 12000K, and colors in a practical range, such as the colors of the blue sky and the sunset, while also allowing Duv to be changed. Furthermore, by using the three colors R, Yw, and Bw, the luminous efficiency of Bw (bluish white) light is higher than that of B (blue) light, which is closer to the chromaticity boundary line, so this has the advantage of making it possible to achieve a relatively good power-luminous flux conversion efficiency (lm / W) compared to the case where light-emitting elements of the three primary colors R, G, and B are used.

[0076] <Embodiment 2> <Application> A camera-linked lighting control system 100B of embodiment 2 is shown in Fig. 7. This is a system that photographs an object with a camera and illuminates the object with light of a color suitable for its color, and general lighting devices 170A and 170B (collectively referred to as general lighting device 170) are added to camera-linked lighting control system 100.

[0077] <Configuration> A general lighting device 170, which is a new component of the camera-linked lighting control system 100B, illuminates the entire room, and is installed, for example, on a ceiling 190 above a passageway.

[0078] The second lighting control device 150 causes the general lighting device 170 to perform a scheduled operation in which the color temperature and dimming rate change according to the time. A graph showing an example of the scheduled operation is shown in FIG. 8, but for simplicity of explanation, only three changes in color temperature are shown, A, B, and C. It is desirable to change the time when the color temperature and dimming rate change according to the time of sunrise and sunset, but FIG. 8 only shows an example of a specific season without considering such changes. In the morning time period A, the color temperature is increased to 5000K (point Z(C) in FIG. 9 described later) and the dimming rate is set to 100% for bright lighting, in the daytime time period B, the color temperature is slightly lowered to 4000K (point Z) and the dimming rate is set to 90%, and in the evening time period C, the color temperature is slightly lowered to 3000K (point Z(W)) and the dimming rate is set to 80%.

[0079] In this embodiment, when changing the color temperature of the general lighting device 170, the color temperature of the object lighting device 160 for the object is also changed. Fig. 9 is a chromaticity diagram for explaining the chromaticity control of the general lighting device and the object lighting device.

[0080] When the chromaticity of the illumination light from the general illumination device 170, which is the overall illumination, is Z(C), Z, or Z(W), the chromaticity of the illumination light from the object illumination device 160, which is the object, is N2(C), N2, or N2(W), respectively. This reduces the difference in chromaticity between the illumination light from the general illumination and the illumination light from the object illumination. Note that the correlated color temperature (T CCT ) change, it is sufficient to make a change in approximately the same direction.

[0081] <Embodiment 3> <Summary> In this embodiment, an experiment is conducted in advance to determine the correlated color temperature that humans perceive as delicious for each type of food, which is the object, and the results are stored in the camera and lighting control device 130. Then, the camera 110 captures the actual object 180, which is food, and performs pixel analysis to control the object lighting device 160 to a correlated color temperature that humans perceive as delicious. Therefore, although the control content differs from the first embodiment, the same hardware as in Fig. 1 is used, and therefore the same reference numerals as in the first embodiment are used for each element.

[0082] <Application> Using this system, it is possible to provide lighting in the food and deli sections of supermarkets that corresponds to the type of food or deli, and in restaurants, it is also possible to provide lighting that corresponds to the type of food, thereby stimulating customers' desire to purchase and increasing customer satisfaction.

[0083] <Experiment on correlated color temperature that makes food taste delicious> In an experiment on correlated color temperature that people find pleasant, 10 types of food (including dishes with unprocessed ingredients such as salads containing carrots, tomatoes, corn, and leafy vegetables) were shown to four subjects, and the correlated color temperature of the lighting on the food was changed while measuring the subjects' brain waves. Based on the subjects' brain waves, the subjects were judged to see whether the food looked delicious or not. The brain wave measurement method was instructed by an expert, and the judgement was also entrusted to an expert. In addition, photos were taken of each dish using automatic exposure, and the average and standard deviation of the R, G, and B values ​​of the pixels were analyzed. However, the R, G, and B values ​​of the pixels each take values ​​between 0 and 255. Based on this, the correlated color temperature that people find delicious was expressed as a function of the RGB values ​​of the pixels.

[0084] Figure 12 shows the relationship between the correlated color temperature of the lighting that makes food taste delicious, obtained from the results of this experiment. The horizontal axis is the correlated color temperature of the lighting, and the photographs of food and the corresponding correlated color temperature that makes them taste delicious are shown. The relationship between food image data and the correlated color temperature of lighting that makes food taste delicious obtained in this experiment is as follows:

[0085]

number

[0086] This method does not identify the type of food and set the correlated color temperature according to the type of food, but adjusts the correlated color temperature based on pixel analysis of the target food. Therefore, it is possible to set a correlated color temperature of lighting that makes any food, even food without a name, taste delicious. Note that it is also possible to use a method that identifies the type of food and sets the lighting to a correlated color temperature that is predetermined according to the food, which allows for more stable lighting control in cases where the type of food is fixed, such as in a restaurant.

[0087] The parameters in this formula are experimental values ​​and therefore will vary depending on the dish or subject; however, we were able to say the following trends:

[0088] In the case of food with a large pixel R value in the photographed area (when Rave is large), for example food with a large area of ​​red or brown, the Rave coefficient is negative, so a low color temperature tends to be preferred.

[0089] In the case of food with many pixel G values ​​in the photographed area (when Gave is large), such as green leafy vegetables, the Gave coefficient is positive, so a high color temperature tends to be preferred. This can be said to be a new finding revealed by this experiment. Previous predictions had been that the effect of a large amount of "green" in a pixel on color temperature would be relatively neutral, in other words, the green coefficient would be small.

[0090] In the case of dishes with many pixel B values ​​in the shooting area (when Bave is large), the coefficient of Bave is negative, so there was no tendency for high color temperatures to be preferred for dishes with many blue components. This is also an unexpected result, but it may be related to the fact that many dishes do not look blue, and that Bave can be high for dishes with high R and G values ​​other than B (for example, rice, which is white).

[0091] Regarding the coefficients of Rsd, Gsd, and Bsd, which indicate the standard deviation (variation) of the R, G, and B values ​​of the pixels in the photographed area, the coefficient of Rsd was positive, the coefficient of Gsd was negative, and the coefficient of Bsd was slightly positive. Therefore, it was found that objects with a large variation in the R values ​​of each pixel in the photographed area (large Rsd) prefer a positive correlated color temperature, while objects with a large variation in the G values ​​of each pixel in the photographed area (large Gsd) prefer a negative correlated color temperature. However, with colorful dishes, Rsd, Gsd, and Bsd all tend to be large, which can result in the effect on CCT being canceled out to some extent.

[0092] <Lighting control to achieve correlated color temperature that makes people feel delicious> In the camera-linked lighting control system 100 shown in Fig. 1, the above formula is entered into the camera and lighting control device 130, or into a computer or server accessible by the camera and lighting control device 130, and the food, which is the object 180, is photographed by the camera 110, and the object region 183 is extracted. In this case, it is preferable to extract only the area where the food is present, for example, the plate portion, as the object region 183, but it is also possible to use the entire deli section of a supermarket or the entire table of a restaurant as the object region 183 and exclude background pixels other than the object. In order to exclude background pixels, there are several methods, such as photographing the background in advance to recognize the characteristics of the background pixels, or manually setting the chromaticity range of the background pixels.

[0093] Derive the average value and standard deviation of the RGB values for each pixel in the target area 183, preferably other than the background, apply them to the above formula, and control the correlated color temperature of the object lighting device 160. By performing such control in a restaurant or a prepared food corner, it is considered possible to make the dishes look delicious and contribute to an increase in customer satisfaction and sales.

[0094] Note that the above formula is merely an example. The key point of this embodiment is to analyze the color components of the pixels in the target area and perform chromaticity control including the control of the correlated color temperature of the illumination light based on the analysis results. At that time, the point of whether each coefficient of the above formula is in the positive direction or the negative direction is also a relatively important point.

[0095] In the above description, it is assumed that a camera having a primary color system filter of any one of R (red), G (green), and B (blue) is used for each pixel. However, a camera having a complementary color system filter of any one of three colors of C (cyan), M (magenta), and Y (yellow) or four colors of C, M, Y, and G may also be used for each pixel.

[0096] <Example of changing Duv as well> In the above experiment, only the CCT was changed, but a preliminary experiment of changing the Duv as well has also been started.

[0097] As a method of changing Duv, there is a method of making it stepwise联动 with the CCT. For example CCT < 3500 → Duv = -6 3500 ≤ CCT < 4000 → Duv = -3 4000 ≤ CCT < 5000 → Duv = 0 5000 ≤ CCT < 5500 → Duv = 3 5500 ≤ CCT → Duv = 6 This is a method of changing Duv stepwise to the negative side when the CCT is small and to the positive side when the CCT is large.

[0098] As a method of changing Duv, there is also a method of making it continuously联动 with the CCT. For example CCT<3500 → Duv=-6 3500≦CCT<5500 → Duv=(CCT-3500)*12 / 2000-6 5500≦CCT → Duv=6 This is a method in which Duv is continuously changed to the negative side when CCT is small, and to the positive side when CCT is large.

[0099] Either method makes the difference in appearance caused by the change in lighting due to different dishes more clear, making the presentation more appealing.

[0100] The above values ​​are just examples. For example, if Duv is on the positive side, it may be disliked if the subject has a slight greenish cast. Therefore, the Duv value may be shifted from the above values, such as by making Duv negative at low CCTs and Duv zero at high CCTs.

[0101] <Embodiment 4> <Basic configuration> 13 shows a configuration diagram of a camera-linked lighting control system 300 according to this embodiment. The camera-linked lighting control system 300 includes a camera 310, a camera / lighting control device 350, an object lighting device 360, and an object 370. The object lighting device 360 ​​is a spotlight, and includes a light body 361, a power supply unit 380, and an arm 375 that connects the light body 361 to the power supply unit 380.

[0102] <Camera> Camera 310 installed on ceiling 390 is connected to camera and lighting control device 350 via control signal 312. Camera 310 captures an object 370, and the image is used to recognize the object within a target area in the image or the chromaticity (color distribution) of the object by an image recognition function in the camera, an external server, or the camera and lighting control device 350.

[0103] <Camera and lighting control device> The camera and lighting control device 350 is composed of a tablet, smartphone, or PC, and runs lighting control software 351. The lighting control software 351 adjusts the light emission intensity of the three color LEDs according to the object or the chromaticity of the object photographed by the camera 310 and recognized by the image recognition function. The light emission intensity conditions of the three color LEDs are transmitted as a wireless control signal 352.

[0104] <Light body> 14 is an explanatory diagram showing the inside of a lamp body 361 surrounded by a frame 367. The lamp body 361 comprises a heat sink 364, a light source 320 placed thereon, a lens 368, and a frame 367. As shown in FIG. 13, light emitted from the light source 320 is radiated by the lens 368 as illumination light 362 at a predetermined radiation angle, and illuminates an object 370.

[0105] <Power supply section> 13, power supply unit 380 is attached to wiring duct rail 395 installed on ceiling 390 by front attachment part 386 and rear attachment part 388, and is supplied with power (the inside of the wiring duct rail is usually not visible, but in this drawing, the wiring duct rail is shown semi-transparently so that the attached state of power supply unit 380 can be seen). Attachment is performed by turning lever 385.

[0106] The power supply unit 380 has a slot for inserting a wireless module 382 , and the wireless module 382 transmits a wireless control signal 352 sent from an external camera / lighting control device 350 to the power supply unit 380 .

[0107] The power supply unit 380 has a 3-channel drive output for independently driving the three color LEDs. The wireless module 382 transmits a control signal to the power supply unit 380, whereby the 3-channel drive output is controlled.

[0108] <Light source> A plan view of the light source 320 used in this embodiment is shown in FIG. 15. The light source 320 is formed by arranging three-color light-emitting elements in a light-emitting region 322 on a substrate 321 having a wiring pattern. As the light-emitting elements, 17 CSP (Chip Size Package) type LEDs 323-1 (E), 17 CSP type LEDs 323-2 (D), and 17 CSP type LEDs 323-3 (F) are arranged as shown in FIG. 15 and are connected in series by wiring inside the substrate. The light source 320 is provided with a mounting hole 325, and is fastened to the heat sink 364 by passing a screw through the mounting hole 325. The light source 320 includes wiring terminals 326-1 (for CSP type LED 323-1), wiring terminals 326-2 (for CSP type LED 323-2), wiring terminals 326-3 (for CSP type LED 323-3), and a wiring terminal 326-0 (common terminal), and is connected to a power supply unit 380 having three outputs, and the light emission of each LED is controlled.

[0109] <Structure of LED> The CSP type LED 323-1, CSP type LED 323-2, and CSP type LED 323-3, which are the light-emitting elements used in the embodiment, include a blue LED chip made of InGaN or the like, and a phosphor-containing resin that covers the side surface and the upper surface of the blue LED chip, and have terminals for passing current through the bottom surface or the side surface of each LED. As the phosphor, one or several of a green phosphor that absorbs the light of the blue LED and emits green light, a yellow phosphor that emits yellow light, and a red phosphor that emits red light are used.

[0110] In each of the above LEDs, as the yellow-based phosphor, for example, (Y 1-x Gd x )3Al5O 12 :Ce 2+ (0 ≦ x ≦ 1) is used. As the green-based phosphor, for example, Lu3Al5O 12 :Ce 2+ is used. As the red-based phosphor, for example, Sr x Ca 1-x AlSiN3:Eu 3+ (0 ≦ x ≦ 1) phosphor, Sr[LiAl3N4]:Eu 2+ or K2SiF6:Mn 4+ phosphor can be preferably used. Quantum dots can also be preferably used.

[0111] <Chromaticity of LED> Figure 16 is a chromaticity diagram (CIE1931 chromaticity coordinate diagram) for explaining the chromaticity of these LEDs, and a line connecting the chromaticity of the blackbody radiation locus is shown as BBL. Also, the correlated color temperature T CT on the BBL, which is the chromaticity that appears to be closest to the color, and a line representing the correlated color temperature T CCT are shown, as well as a line representing the color deviation Duv from the BBL. The chromaticities of the CSP type LEDs 323-1, 323-2, and 323-3, which are the light emitting elements used in this embodiment, are "E" (LED for meat), "D" (LED for bread), and "F" (LED for fresh fish) in Figure 16, respectively. However, "for meat, for bread, for fresh fish" are merely examples, and "E" is also suitable for various objects such as red fruits, and "D" is suitable for fried foods.

[0112] The chromaticity coordinates of the CSP type LED 323-1 (D) are (0.458, 0.407). The chromaticity coordinates of the CSP type LED 323-2 (E) are (0.412, 0.327). The chromaticity coordinates of the CSP type LED 323-3 (F) are (0.358, 0.342). The correlated color temperature T CCT (unit: K (kelvin)) is approximately 2700K for E and D, approximately 4500K for F, and the difference is approximately 1800K.

[0113] The color deviation Duv from the BBL is approximately -1 for D, approximately -31 for E, and the difference is approximately 30. Also, for all three of these LEDs, the color deviation Duv is on the negative side of the blackbody radiation locus (BBL = Black Body Locus).

[0114] , In addition, the chromaticity of each LED can also be expressed in terms of the chromaticity coordinates (u', v') in CIE1976 instead of the chromaticity coordinates (x, y) in CIE1931, and the two can be mutually converted by the conversion formula u' = 4x / (-2x + 12y + 3), v' = 9y / (-2x + 12y + 3). It may also be expressed in other chromaticity coordinate systems.

[0115] In particular, the chromaticity of the CSP LED 323-2 is characterized by a color far from the blackbody radiation locus (BBL), with a color deviation Duv of -31, which is a large absolute value. By combining the CSP LED 323-2 with the CSP LED 323-1 and CSP LED 323-3, which are relatively close to the blackbody radiation locus, the color deviation can be adjusted appropriately.

[0116] By appropriately combining the light from the light-emitting elements CSP type LED 323-1(D), CSP type LED 323-2(E), and CSP type LED 323-3(F), it is possible to obtain light of the chromaticity of the triangle and its interior in Fig. 16. For example, the colors of the points indicated as DE, EF, and EF in the figure can be suitably used to match the ingredients.

[0117] Conventionally, there is color-adjustable lighting that changes color temperature as a type of lighting that combines multiple colors. Color-adjustable lighting changes the "color temperature" along the blackbody radiation locus to adjust between "cool color, high color temperature, fluorescent light color" and "warm color, low color temperature, incandescent light color," realizing lighting that does not feel strange to people. Unlike such "living space" lighting, this embodiment uses lighting that changes the "color deviation from BBL," which feels strange to people, to bring out the color of the object.

[0118] The light-emitting elements CSP type LED 323-1 (D), CSP type LED 323-2 (E), and CSP type LED 323-3 (F) also have characteristic spectra. The spectra of D and F after passing through an optical system such as a lens 368 are shown in FIG. 17, and the spectra of D and E are shown in FIG. 18. Each graph is normalized by the maximum value of G (green) in the wavelength range of 490 to 570 nm. Unlike the synthesis of RGB monochromatic light described later, the spectrum of each light-emitting element has spectral components in the entire wavelength range, but the maximum value of R (red) in the wavelength range of 600 to 660 nm > the maximum value of G (green) in the wavelength range of 490 to 570 nm > the maximum value of Y (yellow) in the wavelength range of 570 to 600 nm, and the shape of Y is suppressed (the maximum value of Y is smaller than the maximum values ​​of R and G), emphasizing red. Therefore, the spectrum obtained by synthesizing D, E, and F also has a relationship of "R>G>Y".

[0119] Figure 17 compares the spectra of D and F by normalizing the light intensity by the maximum value of G, and shows that F, which has a high color temperature, weakens the R component and strengthens the B component compared to D, which has a low color temperature.

[0120] Figure 18 compares the spectra of D and E by normalizing the light intensity by the maximum value of G. It can be seen that E, which has a larger absolute value on the negative side of Duv, has stronger B and R components than D, which has a smaller absolute value of Duv.

[0121] It should be noted that the vertical axis in Figures 17 and 18 represents light intensity and does not take luminosity into consideration. The luminosity coefficients in the CIE1931 relative luminosity curve are 0.06472 at a wavelength of 450 nm (B), 0.95447 at a wavelength of 540 nm (G), 0.89636 at a wavelength of 580 nm (Y), and 0.29803 at a wavelength of 630 nm (R), with the coefficients for G and Y being close to 1 and the coefficients for B and R being small. Therefore, the impact of the G and Y components on the overall appearance of the color is large.

[0122] Taking such points into consideration, in the spectrum of each color, the maximum value of Y (a value that does not consider luminosity) should be 0.25 or more, and more preferably 0.5 or more, with the maximum value of G being 1. On the other hand, it is good that the maximum value of Y is below the line connecting the maximum values ​​of G and R, and the Y component is suppressed, and it is more preferable that the maximum value of Y is below the maximum value of G.

[0123] Figure 19 will be used to explain the difference between the method that uses light-emitting elements of three colors, D, E, and F, which have characteristic spectra, and the RGB (red, green, blue) method, which can in principle produce all colors. In Figure 19, R is red, G is green, and B is blue. Since all colors can be obtained using RGB, one might wonder if there is no difference from the RGB method using the three colors D, E, and F, but as Figure 19 shows, the area surrounded by the three colors D, E, and F is extremely small compared to the area surrounded by the three colors RGB.

[0124] FIG. 20 shows a schematic diagram for explaining color unevenness. The light source 320' is composed of three color LEDs (E, F, G) and irradiates a white object 370' through a lens 368'. At that time, the light from the three LEDs does not completely overlap, so there are parts shown as D-rich, E-rich, and F-rich. If a light source of the primary colors of "RGB" were used, these parts would be R-rich, G-rich, and B-rich, but since R, G, and B are different primary colors, color unevenness would be noticeable. In the present invention, by using three color LEDs in a limited chromaticity range instead of a primary color light source, the chromaticity difference in the parts where the light does not overlap sufficiently is small to begin with, and color unevenness is essentially reduced.

[0125] By using D, E, and F lighting, which contain not only R, G, and B components but also a moderate Y component and have spectra that are originally suitable for object lighting, or lighting with a mixture of these colors, the camera can identify various foods, such as red and yellow fruits, green vegetables, red meat, sashimi, and salmon, blue-backed fish, and brown bread, baked goods, and fried foods, and provide lighting suitable for each food. Although this object lighting system was developed with food ingredients in mind, it has been shown to look beautiful when used to light a variety of objects, such as clothing, car bodies, furniture, small items, and flowers. However, there are cases where a color looks beautiful in the store but different at home, so it is preferable to adjust and add light such as E, which has a large absolute value of color deviation from the BBL. This object lighting system is convenient because it allows fine adjustment of the amount of color deviation, that is, how the color appears, by "mixing colors."

[0126] Furthermore, in light source 320 shown in FIG. 15, the chromaticity difference between the three color LEDs arranged in light emitting area 322 is small, which has the advantage that color unevenness when irradiated onto an object is small and almost unnoticeable.

[0127] The correlated color temperature T of each light-emitting element used in the present invention CCT is 2000K or higher, preferably 2500K or higher, and 6000K or lower, preferably 5000K or lower.

[0128] The color deviation Duv (1000 times the color deviation duv) from the BBL of each light-emitting element used in the present invention is -50 or more (absolute value 50 or less), preferably -40 or more (absolute value 40 or less), +20 or less, preferably +10 or less, and the difference in color deviation between two light-emitting elements with the largest difference in color deviation is preferably 50 or less, and preferably 40 or less. By using light-emitting elements with such limited color deviation, color unevenness can be reduced. On the other hand, in order to accommodate targets of various colors, the color deviation between two light-emitting elements with the largest difference in color deviation is preferably 10 or more, preferably 20 or more, and more preferably 30 or more.

[0129] The correlated color temperature T of the light-emitting element with the lowest color temperature (D in the fourth embodiment) and the light-emitting element with the highest color temperature (F in the fourth embodiment) used in the present invention CCT In order to accommodate objects of various colors, the difference should be 400 K or more, preferably 800 K or more, and more preferably 1200 K or more. On the other hand, from the viewpoint of reducing color unevenness, the difference should be 3000 K or less, and preferably 2000 K or less.

[0130] <Embodiment 5> <Basic configuration> 21 shows an object lighting device 560 used in the camera-linked lighting control system according to this embodiment. The object lighting device 560 is a spotlight, and comprises a light body 561, a power supply unit 580, and an arm 575 that connects the light body 561 to the power supply unit 580, and can be connected to a wiring duct rail. In order to wirelessly control the emitted light color, the power supply unit 580 is provided with a wireless module 582, which is a detachable wireless transceiver, and the emitted light color is changed using a camera / lighting control device 350 connected to the camera 310.

[0131] <Light body> 22 is an exploded perspective view of a lighting body 561. The lighting body 561 includes a heat sink 564, a printed circuit board 521 placed thereon, a multi-lens 566, and twelve lenses 568 integrally molded within the multi-lens. Twelve surface-mounted LEDs 523 are mounted on the printed circuit board 521, and each of the surface-mounted LEDs 523 corresponds to a lens 568.

[0132] <Light source> FIG. 23 is a chromaticity diagram for explaining the chromaticity of an LED. The surface mount type LED 523 has B27 (2700K), A27 (T CCT =2700K, Duv=-10), B46(4600K), A46(T CCT The LEDs are each made up of three of four colors (T = 4600K, Duv = -10). This allows the colors in the square shown in Figure 23, for example AW30 (T CCT =3000K,Duv=-4),AW35(T CCT =3500K,Duv=-5),AW42(TCCT =4200K, Duv=-5).

[0133] As an example of a spectrum obtained by combining each color in Fig. 23, AW35, i.e. T CCT FIG. 24 shows the composite spectrum of 3500K. The blue component around 450nm is indicated by B, the green component around 550nm is indicated by G, the yellow component around 590nm is indicated by Y, and the red component around 630nm is indicated by R. In the clothing field, in order to show the object in a natural color appearance, it is preferable that there is light in the entire spectrum range and the color rendering index Ra is 90 or more, more preferably 93 or more, and even more preferably 95 or more. Under such conditions, considering that whitish colors that look less yellow are preferred in the clothing field, the Y component is slightly reduced and the R component is increased compared to the typical high color rendering LED shown by the dotted line in FIG. 23. As a result, the color temperature does not change much, and the color deviation Duv is about -5. The half-width shown by the dotted line is about 180nm, but it is preferable that it is 150nm or more, and in particular, when the peak of R is 100%, Y (590nm) is 50% or more, preferably 60% or more, and more preferably 70% or more.

[0134] Here, the difference in color deviation Duv between the first light-emitting element designated B and the second light-emitting element designated A is preferably 5 or more, more preferably 10 or more, while for objects that are often seen under normal lighting, such as clothing, car bodies, furniture, small items, and flowers, the difference in Duv is preferably 15 or less, so that little sense of incongruity is created when illuminated by this object lighting device and when illuminated by a normal object lighting device. For food products, the difference in Duv is set to 15 or more, with an emphasis on how the colors look in the store, and it is preferable to make meat and red fruit look particularly attractive.

[0135] As an example of controlling chromaticity in clothing, first, the clothing category or chromaticity distribution is analyzed based on the color tendency used in the clothing photographed by a camera. In general, it is said that lighting control should be performed with a high color temperature for summer clothing and casual clothing, and a low color temperature for winter clothing and luxury clothing. Also, if you want to emphasize red, it is better to set Duv to the negative side. For this type of camera-linked lighting control, it is desirable to fine-tune the control program according to orders based on the brand image of the clothing store.

[0136] <Embodiment 6> <Application> The configuration of a camera-linked lighting control system 600 of this embodiment is shown in Fig. 25. This is a camera-linked lighting control system that photographs clothing as an object with a camera and illuminates the object with light of a color suitable for the color of the object.

[0137] <Configuration> The camera-linked lighting control system 600 includes a camera 610 installed on a ceiling 690, a camera and lighting control device 630, an object lighting device 660, a gateway 655, and a camera control device monitor 632 that is placed at the user's hand.

[0138] <Camera and camera / lighting control device> The camera 610 captures an image 613 of an object 680 within its field of view 612 and transmits it to a camera and lighting control device 630 via a communication line 617 .

[0139] The camera and lighting control device 630 is a device having a camera control function and a lighting control function, and also has an image recognition function. The function is realized by a computer, which is hardware, and software. As an output device, for example, a camera control device monitor 632 is provided, which displays an image 613 and control contents. The camera and lighting control device 630 is connected to a gateway 655 via a communication line 657.

[0140] <Gateway> The gateway 655 transmits the lighting control signals to the object lighting device 660 via wireless communication 654 .

[0141] <Object Illumination Device> The object illuminator 660 is, for example, a spotlight, and illuminates an object 680 (an object 680F, which is clothing in this case) in an object area 683 with illumination light 662. The object illuminator 660 can change the chromaticity of the illumination light, and in particular can change the color deviation Duv, which is an element other than color temperature. Such control of the chromaticity of the illumination light is performed using the camera and illumination control device 630.

[0142] <Operation overview> The operation flowchart of the camera-linked lighting control system 600 is shown in Figure 26. In the first step, the lighting device is turned on to illuminate the object. In the second step, the object is photographed with a camera and an image is acquired. In the third step, image segmentation, which will be described below, is performed to extract the object image region. In the fourth step, the colors within the object image region are divided using 4-way clustering (divided into four groups of similar color). In the fifth step, the average image of the object image region is calculated by taking a weighted average of the chromaticity and area of ​​each cluster. In the sixth step, the object is illuminated with illumination light according to the average chromaticity of the object image region (this is referred to as the "chromaticity of the object image region" or "object color").

[0143] <Identifying object image regions using image segmentation> Image segmentation, which is an AI technology, is used to identify the area of ​​the clothing that is the object. Fig. 27 is an explanatory diagram of image segmentation. Fig. 27(a) shows a part of an image captured by a camera 610. From this captured image, the area of ​​the object reflected in the image is extracted as object image area F in Fig. 27(b), and the object is identified for the part specified by object image area F. To achieve high prediction accuracy in image segmentation, learning data is necessary. Here, learning to recognize the shape of clothing is performed in advance, and the image processing device (a software function of the camera and lighting control device 630, or a software function of an external server accessed by the camera and lighting control device 630, or an independent dedicated image processing device) refers to the learning data to identify which parts of the image are clothing and sets them as the object image area F.

[0144] As described in detail in the seventh embodiment, by referring to the learning data, it is possible to not only simply identify that the object is clothing, but also to identify the type and color of the clothing, such as a white shirt, a navy blue jacket, a red cardigan, and red and blue mixed pants, and the lighting system may irradiate lighting light according to the identified type and color of the clothing. The learning data used in this case may be stored in the camera and lighting control device 630 equipped with an image recognition function, or may be stored in an external server.

[0145] <Identifying the color of objects> An object image region F determined to be "clothing" may include, for example, the entirety of a blue jacket and a white shirt. Therefore, multi-division clustering is performed to classify the regions into groups with similar hues, such as F1 and F2 in FIG. 27(b), and the average chromaticity is calculated. Note that the number of divisions in multi-division clustering is preferably between 2 and 6, and in this study it was set to 4. With current technology, a division number of 6 or less tends to result in fast processing speeds and fewer classification errors, since the amount of information is not excessively large.

[0146] For simplicity, we will explain this as a two-division clustering. The chromaticity coordinates (x1, y1) of the first color and the number of pixels a1, which is its area, are calculated, and the chromaticity coordinates (x2, y2) of the second color and the number of pixels a2, which is its area, are calculated. From these, the average chromaticity is (x f , y f )=(a1(x1,y1)+a2(x2,y2)) / (a1+a2) It is calculated as:

[0147] This "multi - segmentation clustering" is the same technology as the one described as the K - means method, which, in "S10. Object Recognition" above, classifies each pixel of an image into N (N is an integer greater than or equal to 2) color regions from the image data of the object, extracts a representative color with the average value of the region with the largest number of pixels existing in the classified color space as the representative color, and recognizes what the object is from the representative color. Here, since the object image region is narrowed down using AI in advance and the representative color is extracted for it, the object can be judged more appropriately.

[0148] <Illumination with chromaticity according to the object> The camera - illumination control device 630 sets the reference chromaticity coordinates as (x w , y w ), and controls the object illumination device 660 so that the color of the illumination light is a color closer to the color of the above - mentioned clothes (x f , y f ) than white, for example, a color of chromaticity (x w + k(x f - x w ), y w + k(y f - y w ), where 0 < k ≤ 1. The object illumination device 660 illuminates with that color. However, if the color of the illumination light obtained here does not change much from the current color of the illumination light, it may be acceptable not to perform illumination control in order to avoid fine changes in the color of the illumination light.

[0149] The reference chromaticity coordinates may be, for example, white (0.33, 0.33) or the chromaticity coordinates of the illumination light of the initial illumination. Also, if it is desired to emphasize the freshness by illuminating summer clothes with bluish light, for example, the reference chromaticity coordinates may be, for example, (0.38, 0.38) or (0.43, 0.40) which are black - body radiations of about 4000K.

[0150] In the above example, the chromaticity coordinates according to CIE1931 were used. However, since CIE1931 is a coordinate system where the difference in coordinates and the color difference felt by people are different, other chromaticity coordinate systems, for example, the uv coordinate system according to CIE1960 or the u'v' chromaticity coordinate system according to the aforementioned CIE1976 may be used. That is, the reference chromaticity coordinates may be (u‘w , v' w ) and the color of the lighting is made slightly closer to the color of the clothing than white, for example, chromaticity (u' w +k(u' f -u' w ), v' w +k(v' f -v' w )), but 0 <k≦1としてもよい。

[0151] <Embodiment 7> <Application> The camera-linked lighting control system 600 of this embodiment is the same as that of the sixth embodiment, and therefore a description thereof will be omitted. However, the image processing is targeted at "meat 680M in a tray 681T" as shown in Fig. 28. Assuming that the meat 680M is wrapped, a price tag label 681L1 or a label 681L2 indicating a sale or the like may be attached, and these need to be removed by image processing.

[0152] <Identifying object image regions using image segmentation> Image segmentation, which is an AI technology, is performed to identify the area of ​​meat, which is the object. FIG. 29 is an explanatory diagram of image segmentation. FIG. 29(a) shows a part of an image captured by a camera 610. From this captured image, the area of ​​the object reflected in the image is extracted as object image area M in FIG. 29(b). The image processing device identifies what object the part specified by object image area M is. A large amount of training data is necessary to achieve high prediction accuracy in image segmentation. Here, training to recognize meat is performed in advance, and the image processing device identifies which parts of the image are meat or not based on the discrimination ability obtained from the training data, and sets them as the object image region M. At that time, the image processing device determines that the labels 681L1 and 681L2 are not objects.

[0153] <Identifying the color of objects> For the object image region M determined to be "meat" by image segmentation, the image processing apparatus obtains the average color of the pixels in the region by performing multi - segmentation clustering as necessary (it may not be performed). Let the chromaticity coordinates of the average color be (x m , y m ).

[0154] <Illumination with chromaticity according to the object> The first control method is that the camera - illumination control device 630 sets the reference chromaticity coordinates as (x w , y w ), makes the color of the illumination light closer to the color of meat than white, for example, the chromaticity (x w +k(x m -x w ), y w +k(y m -y w )) where 0 < k ≤ 1, and controls the object illumination device 660. The object illumination device 660 performs illumination of that color.

[0155] The second control method is to identify the type of meat, specifically, lean beef, marbled beef, cut - off pork, pork for cutlets, chicken thigh meat, chicken wing tips, etc. by image segmentation and multi - segmentation clustering as necessary. In this case, information on the distribution of red meat and white fat can be used by multi - segmentation clustering. According to the recognized type of meat of the object, the object illumination device 660 illuminates the object 680 with the chromaticity corresponding to the preset type of meat. The flow in this case is shown in FIG. 30.

[0156] Lighting control using a method for identifying the object image area, such as image segmentation, has the advantage that it is not affected and the color of the lighting does not change even if the number of objects decreases and the proportion of the background in the image increases, for example, when meat is sold and there is little left. For example, Fig. 31(a) is a photo of a refrigerated case with trays of meat, and Fig. 31(b) is a photo in which the meat area has been extracted by image segmentation (image segmentation is performed by dividing the case into the upper half and the lower half). With this method, the same lighting control can be performed regardless of the number of trays of meat. Note that when the number of trays becomes zero, control such as lowering the dimming rate of the lighting, turning off the lighting, or changing the color of the lighting to the standard color (the color before it was used for meat) may be performed.

[0157] <Modifications and other changes> The above describes an embodiment of the lighting device according to the present invention. However, the exemplified lighting device can also be configured as follows, for example, and it goes without saying that the present invention is not limited to the lighting device as shown in the above embodiment.

[0158] (1) The illustration of the object lighting device 160 shown in the figure is based on the image of a spotlight, and the illustration of the general lighting device 170 is based on the image of a square-shaped recessed lighting device, but the shapes are not limited to these and may be other lighting devices, such as downlights, universal downlights whose direction of illumination can be changed, linear base lights, floodlights, flexible tape lights, and the like.

[0159] (2) General lighting equipment may be used for indoor or outdoor lighting, and may be installed anywhere.

[0160] (3) When the three primary colors R (red), G (green), and B (blue) are used as the colors of 3CH, the blue color may be a color that satisfies y<0.4 and x<0.2 and is closer to the chromaticity boundary line E than blue-white, and the green color may be a color that satisfies y>0.4 and is not yellow-white or blue-white.

[0161] (4) The color of the illumination light before object recognition is not limited to the color of point Z (color temperature 4000K). For example, if the object is meat, it may be set to a color on the blackbody radiation locus of 3500K in advance, and if the object is fish, it may be set to 5000K. Note that, although the color is on the blackbody radiation locus, if the absolute value of Duv is 1 or less, it may be considered to be a "color on the blackbody radiation locus."

[0162] (5) A lighting control signal may be sent directly from the lighting control device to the lighting device without using a gateway, which is a wireless communication repeater.

[0163] (6) The wireless communication method may be, for example, Bluetooth (registered trademark) or Wi-Fi (registered trademark).

[0164] (7) The camera and lighting control device is a device that combines a camera control function such as capturing images with a camera, an image recognition function such as segmenting an object area and recognizing an object, and a lighting control function such as lighting control based on object recognition. Although an example is described in which these three functions are realized by software in one computer, these three functions may be handled by another device, for example, the function of the above-mentioned "lighting control device" may be provided in a "second lighting control device", the function of the "image recognition function" may be built into a camera, or may be realized by a server on a network not shown in the figure. In other words, the "device" or "function" in this specification is not limited to simple hardware, but also refers to a combination of hardware and software, and the place where the function is realized is not limited to the places exemplified in this application.

[0165] (8) The light-emitting element is not limited to an LED, but may be an organic electroluminescent (EL) element (organic LED), an element in which the phosphor and excitation light source are separated, an element that uses discharge, an element that is excited by an electron beam, or any other element that emits light.

[0166] (9) As the LEDs of each color, in the fourth embodiment, CSP type LEDs are mounted on one board, and in the fifth embodiment, SMD (Surface Mount Device) type LEDs are mounted on a printed board, but COB type LEDs may be used in which blue LED chips are arranged on a board and multiple blue LED chips are covered with a resin containing phosphor. These LEDs can also be used in the first to third embodiments.

[0167] (10) Although examples have been given of three-color LEDs and four-color LEDs as light sources using LEDs of multiple light colors, it is also possible to use only two-color LEDs with different color deviations (for example, D and E, F and E in embodiment 4, and A46 and B27 in embodiment 5).

[0168] (11) The chromaticity of each LED in the embodiment is an example, and other chromaticities may be used.

[0169] (12) Although the example of wireless control has been given as the method for controlling the light color of the object lighting device, wired control may also be used.

[0170] (13) In this application, the term "object" is used to include not only "merchandise" but also "non-sale items" such as works of art and antiques in a museum and children's paintings at an exhibition.

[0171] It should be noted that the above-described embodiments disclosed herein are illustrative in all respects and are not intended to be a basis for a restrictive interpretation. Therefore, the technical scope of the present invention is not interpreted solely by the above-described embodiments, but is defined based on the claims. Also, all modifications within the scope and meaning equivalent to the claims are included. [Explanation of symbols]

[0172] 100, 100B, 300, 600 Camera linked lighting control system 110, 310, 610 Camera 112, 612 field of view 113, 613 images 117, 617 communication line 130, 350, 630 Camera and lighting control device 132, 632 Monitor for camera control device 150 Second lighting control device 152, 154, 654 Wireless communication 155, 655 Gateway 157, 657 communication line 160, 160A, 160B, 360, 560, 660 Object Illumination Device 162, 162A, 162B, 362, 662 illumination light 170, 170A, 170B General lighting equipment 180, 180A, 180B, 370, 680, 680F, 680M Target 182, 182A, 182B background 183, 183A, 183B Target Area 184 QR Code 185 LED Signal Transmitter 190, 390, 690 ceiling 312, 352 Control Signals 320 light source 321 Substrate 322 Luminous Area 323 CSP type LED 325 mounting hole 326 Wiring terminal 351 Lighting Control Software 361, 561 light body 364, 564 Heatsink 367 slots 368, 568 Lens 375, 575 Arm 380, 580 power supply section 382, 582 Wireless Module 385 Lever 386 Front mounting part 388 Rear mounting part 395 Wiring Duct Rail 521 Printed Circuit Board 523 Surface Mount LED 566 Multi Lens F, M Object image area

Claims

1. A camera-linked lighting control system including a camera, a device having an image recognition function, a lighting control device, and an object lighting device, The object lighting device illuminates an object area where an object may exist with a first illumination light, The camera photographs the target area to obtain an image including a background and the target object; The device having the image recognition function extracts an object image area that is an area of ​​the object from the image, and recognizes the type or color of the object from the object image area; the lighting control device sets a chromaticity of the second illumination light in accordance with a type or a color of the object; The camera photographs the target area again to obtain an image including the background and the target again; the object lighting device irradiates the object region with the same second illumination light even when a ratio of an area of ​​the object image region to an area of ​​the background in the image acquired again becomes smaller than a ratio of an area of ​​the object image region to an area of ​​the background in the image acquired previously. Camera-linked lighting control system.

2. The device having the image recognition function calculates an average chromaticity of the object image area from the object image area, and recognizes the average chromaticity as the color of the object. The camera-linked lighting control system according to claim 1 .

3. The average chromaticity is an average chromaticity obtained by dividing the object image region into color regions of a plurality of representative colors and calculating a weighted average of the chromaticity and area of ​​each color region.

3. The camera-linked lighting control system according to claim 2.

4. The device having the image recognition function identifies the object image area in the image and recognizes the type of the object by referring to learning data for image recognition. The camera-linked lighting control system according to claim 1 .

5. The first illumination light has chromaticity on the blackbody radiation locus. The camera-linked lighting control system according to claim 1 .

Images