Recognition system

Abstract

To provide a recognition system which can accurately recognize objects having plural types.SOLUTION: A recognition system of a chip in a game parlor having a game table includes a game recording device which records a state of the chips stacked on the game table as an image using a camera and a chip determination device which analyzes an image of the state of the recorded chips to determine the number and the type of the chips bet by a player. The chip determination device has a function of storing a characteristic of an image of a predetermined state of the chip, and of outputting and displaying, as a determination result, a fact of an unclear determination when the image obtained from the game recording device at the time of determining is the image of the predetermined state.SELECTED DRAWING: Figure 3

Description

[Technical field]

[0001] The present invention relates to a recognition system, and in particular to a chip recognition system. [Background technology]

[0002] In games such as baccarat, customers (players) place bets by stacking multiple chips on the table. Therefore, it is necessary to accurately identify the stacked chips. International Publication No. 2008 / 120749 discloses an example of chips used in the game. Summary of the Invention

[0003] An object of the present invention is to provide a recognition system capable of accurately recognizing multiple types of objects.

[0004] The chip recognition system according to the first aspect comprises: A chip recognition system for an amusement facility having a gaming table, comprising: a game recorder for recording the state of the chips stacked on the gaming table as an image using a camera; a chip determination device that performs image analysis of the recorded chip state images to determine the number and type of chips bet by a player; Equipped with The chip judgment device further has a function of storing the characteristics of an image of a predetermined chip state, and when it is determined that the image obtained from the game recording device at the time of judgment is an image of the predetermined state, outputting and displaying the result of the judgment as unclear.

[0005] According to this aspect, the chip determination device stores, for example, an image that reduces the accuracy of chip reading as an image of a predetermined state, and when it determines that the image obtained from the game recording device is an image of such a predetermined state at the time of determination, it outputs and displays an uncertain determination, rather than forcing an answer. This makes it possible to exclude from the determination results of the number and type of chips a determination result that is forcibly given for an image that reduces the accuracy of chip reading (i.e., a determination result that is likely to be incorrect). In other words, it becomes possible to determine the number and type of chips only from images that can be read accurately, and as a result, it becomes possible to recognize chips with high accuracy.

[0006] A chip recognition system according to a second aspect is a chip recognition system according to the first aspect, The chip determination device includes an artificial intelligence device, and the artificial intelligence device learns a plurality of images used in past determinations when a determination error occurs in the chip determination device as training data, The chip determination device further has a function of self-determining the accuracy of the determination based on images in which an error in the determination result has occurred as a result of the learning, and outputting and displaying the result of the determination as unclear for images in which there is doubt about the determination.

[0007] According to this aspect, the artificial intelligence device of the chip judgment device can improve the accuracy of self-judgment by learning from multiple images used in past (incorrect) judgments when there was an error in the judgment, which can reduce the situation where an image that can be read correctly is erroneously output and displayed as an unknown judgment. It can be done.

[0008] A chip recognition system according to a third aspect is a chip recognition system according to the second aspect, The chip determination device further has a function of, when it determines that a chip is uncertain, analyzing images from the game recording device to determine and store whether the cause of the determination that the chip is uncertain is that the chips are stacked on the gaming table overlap, or that part of or the entire chip is hidden by another chip.

[0009] According to this embodiment, the dealer can easily confirm the cause of the unclear judgment from the judgment result stored in the chip judgment device. This allows the dealer to quickly resolve the cause of the unclear judgment by rearranging the chips so that they are not shaded by other chips, or by rearranging the chips that are stacked in a jagged shape (if the player does not like the dealer touching the chips, the dealer may warn the player).

[0010] A chip recognition system according to a fourth aspect is a chip recognition system according to any one of the first to third aspects, The game recording device records images acquired from the camera with an index or time stamp, or with a tag identifying the stacking state of the chips, so that the record of the game can be later analyzed by the chip judgment device.

[0011] According to this aspect, the chip judgment device can easily identify an image of the chip state to be analyzed from the recorded contents of the game recording device by using the index, time, and tag assigned to the image, thereby reducing the time required for identification.

[0012] A chip recognition system according to a fifth aspect is a chip recognition system according to any one of the first to fourth aspects, The chip judgment device includes a second artificial intelligence device, and the second artificial intelligence device learns, as training data, a plurality of images and chip information used in past judgments when the judgment in the chip judgment device was correct.

[0013] According to this embodiment, the second artificial intelligence device of the chip judgment device learns from multiple images and chip information used in past (correct) judgments made by the chip judgment device as training data, thereby improving the accuracy of judgment when determining the number and type of chips.

[0014] A chip recognition system according to a sixth aspect is a chip recognition system according to any one of the first to fifth aspects, When the chip determination device itself determines that the determination is unclear, it performs image analysis on an image recorded by a camera other than the camera to determine the number and type of chips bet by the player.

[0015] A chip recognition system according to a seventh aspect is a chip recognition system according to any one of the first to sixth aspects, When the chip determination device recognizes the next chip without recognizing a chip at a certain interval or more in the vertical direction, it determines that the image is in the specified state, and outputs and displays the result of the determination as unclear.

[0016] A chip recognition system according to an eighth aspect is a chip recognition system according to any one of the first to seventh aspects, The chip determination device compares the number of chips determined from the chip height with the number determined by image analysis of the image of the chip state, and if they differ, it determines that the image is in the specified state and outputs and displays a determination result indicating that the determination is unclear.

[0017] A recognition system according to a ninth aspect includes: A recognition system in which a plurality of types of objects are identified and the number of objects of each type is determined, A recording device that records the state of the object as an image using a camera; A determination device including an artificial intelligence device that performs image analysis on the recorded images of the objects to determine the number of each type of object; Equipped with The judgment device learns past judgment results as teacher data, and has a function of self-judging the accuracy of the judgment, and further has a function of self-judging that the judgment result is doubtful if the level of accuracy is below a certain level, and outputting and displaying that the judgment result is unclear.

[0018] According to this aspect, the judgment device learns past judgment results as teacher data, and for a new image, first, it judges the accuracy of the judgment by itself, and if the level of accuracy is below a certain level, it outputs and displays the judgment as unclear, rather than forcing an answer. This makes it possible to exclude judgment results when a forced answer is given for an image with low judgment accuracy (i.e., judgment results that are likely to be incorrect) from the judgment results of the number of each type of object. In other words, it becomes possible to judge the number of each type of object only from images that can be read accurately, and as a result, it becomes possible to recognize objects with high accuracy. [Brief description of the drawings]

[0019] [Figure 1] FIG. 1 is a diagram showing a schematic diagram of a gaming center equipped with a chip recognition system according to one embodiment. [Diagram 2] FIG. 2 is a diagram for explaining the progress of a baccarat game. [Diagram 3] FIG. 3 is a block diagram showing a schematic configuration of a chip recognition system according to an embodiment. [Figure 4] FIG. 4 is a flowchart for explaining a chip recognition method according to an embodiment. [Diagram 5] FIG. 5 is a diagram for explaining a case where a chip is hidden behind another chip. [Figure 6] FIG. 6 is a diagram for explaining a case where the chips are stacked in a jagged manner. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0020] Hereinafter, an embodiment of the present invention will be described in detail with reference to the accompanying drawings. In each drawing, components having equivalent functions are denoted by the same reference numerals, and detailed description of the components having the same reference numerals will not be repeated.

[0021] In the embodiment described below, a chip recognition system in an amusement arcade having gaming tables will be described as an example of a recognition system that distinguishes objects by type and determines the number of each type. However, it goes without saying that the object to be judged is not limited to chips as long as it has multiple types.

[0022] First, a game played in a gaming facility having a gaming table 4 will be described with reference to Fig. 1 and Fig. 2. In this embodiment, the gaming table 4 is a baccarat table, and an example in which a baccarat game is played will be described, but the present invention can be applied to other gaming facilities or other games. It is Noh.

[0023] FIG. 1 is a diagram showing a schematic diagram of a gaming facility equipped with a chip recognition system 10 according to an embodiment. As shown in FIG. 1, the gaming facility has a substantially semicircular gaming table 4 and a plurality of chairs 201 arranged along the arc side of the gaming table 4 so as to face a dealer D. The number of chairs 201 is arbitrary, and in the example shown in FIG. 1, six chairs 201 are arranged. In addition, betting areas BA are provided on the gaming table 4 in correspondence with the respective chairs 201. That is, in the example shown, six betting areas BA are arranged in an arc shape.

[0024] As shown in Fig. 1, a customer (player) C sits on each of the chairs 201. The customer (player) C bets on whether the outcome of the baccarat game will be a win for the player (PLAYER) or the banker (BANKER), or whether the game will end in a draw (TIE), by stacking and placing chips W on a betting area BA provided in front of the chair 201 where the customer (player) C sits (hereinafter, this will be referred to as a "bet").

[0025] The chips W to be bet may be of one type or multiple types. The number of chips W to be bet may be determined arbitrarily by the customer (player) C. The chip recognition system 10 according to this embodiment recognizes the number and types of the chips W arranged in a stack.

[0026] In order to end the betting by customer (player) C, dealer D waits for the right timing to call "No More Bets" and moves his hand sideways. Next, dealer D draws cards one by one from the card shooter device S onto the gaming table 4. As shown in FIG. 2, the first card becomes the player's hand, the second card becomes the banker's hand, the third card becomes the player's hand, and the fourth card becomes the banker's hand (hereinafter, drawing the first to fourth cards will be referred to as "dealing").

[0027] All cards are drawn from the card shooter S with their backs facing up. Therefore, neither the dealer D nor the customer (player) C can know the rank (number) or suit (heart, diamond, spade, club) of the drawn cards.

[0028] After the fourth card is drawn, the customer (PLAYER) C who bet on PLAYER (if there are multiple customers who bet on PLAYER, the customer C who bets the highest amount, or the dealer D if there are no customers who bet on PLAYER) turns the first and third cards, which are face down, face up. Similarly, the customer (PLAYER) C who bet on BANKER (if there are multiple customers who bet on BANKER, the customer C who bets the highest amount, or the dealer D if there are no customers who bet on BANKER) turns the second and fourth cards face up (this turning of the back cards face up is generally called a "squeeze").

[0029] Then, based on the ranks (numbers) of the first through fourth cards and the detailed rules of the baccarat game, dealer D draws the fifth and sixth cards, which become the player's or banker's hand, respectively. Similarly, customer C who bet on the player squeezes the cards that will be in the player's hand, and customer C who bets on the banker squeezes the cards that will be in the banker's hand.

[0030] After the first four cards are drawn, squeeze the fifth and sixth cards to win or lose. The time it takes for the result to become clear is the most exciting part for customer (player) C.

[0031] Furthermore, depending on the rank (number) of the cards, the outcome may be decided by the first four cards, or it may take the fifth or even sixth card to decide the outcome. The dealer D determines whether the outcome has been decided or not based on the rank (number) of the squeezed cards, and presses the win / loss result display button on the card shooter device S to display the result on the monitor to inform the customer (player) C.

[0032] At the same time, the outcome of the game is determined by a winning / losing determination section of the card shooter device S. If the dealer D attempts to draw another card without displaying the winning / losing result even though the winning / losing result has been determined, an error occurs. The card shooter device S detects the error and outputs an error signal. Finally, while the winning / losing result is being displayed, the dealer D settles the chips bet by the customers (players) C, pays the winning customers (players) C, and collects the chips bet by the losing customers (players) C. After the settlement is completed, the display of the winning / losing result ends and betting for the next game begins.

[0033] The above-mentioned flow of a baccarat game is widely practiced in general casinos, and the card shooter device S is an existing card shooter device that has a structure in which cards are drawn by the dealer D, is configured to read the drawn cards, and further has a result display button and a result display unit, and is equipped with the function of judging win / loss and displaying the win / loss result. On a general casino floor, a card shooter device S and a monitor are arranged for each of the multiple gaming tables 4 lined up, and the cards to be used are supplied to each gaming table 4 or the cabinet below it in packages or sets, or even cartons, and are operated.

[0034] The chip recognition system 10 according to the present embodiment relates to a system for recognizing chips W that a customer (player) C has piled up and placed in a betting area BA, and more specifically, to a system for recognizing the number and / or type of chips W.

[0035] 1, in this embodiment, a surveillance camera 212 for capturing images of the chips W stacked in the betting area BA is provided outside the gaming table 4. Each chip W is provided with an RFID, and a chip tray 23 managed by the dealer D is provided with an RFID reader 22 for reading the RFIDs of the chips W in the chip tray 23.

[0036] The chip recognition system 10 according to this embodiment is communicatively connected to a surveillance camera 212 and an RFID reader 22, respectively.

[0037] Fig. 3 is a block diagram showing a schematic configuration of a chip recognition system 10 according to this embodiment. As shown in Fig. 3, the chip recognition system 10 includes a game recording device 11, a chip judgment device 12, and a judgment correctness determining device 14. At least a part of the chip recognition system 10 is realized by a computer.

[0038] The game recording device 11 includes a fixed data storage such as a hard disk. The game recording device 11 records the state of the chips W stacked on the game table 4 as an image captured by the camera 212. The image may be a moving image or a series of still images.

[0039] The game recorder 11 assigns an index or time stamp to the images captured by the camera 212 so that the game record can be later analyzed by the chip judgement device 12 described later. Alternatively, a tag specifying the scene of collecting or paying the tip W may be added and recorded.

[0040] The chip determination device 12 performs image analysis on the image of the state of the chips W recorded in the game recording device 11 to determine the number and type of chips W bet by the customer (player) C. The chip determination device 12 may include an artificial intelligence device that performs image recognition using, for example, deep learning technology.

[0041] However, if the chips W1 to W6 bet by customer (player) C are stacked in multiple piles (see Figure 5) or if the chips W1 to W6 are stacked in a messy and jagged manner (see Figure 6), the camera 212 cannot see the entire chips W1 to W6, which may reduce the accuracy of reading the chips W1 to W6.

[0042] More specifically, if the height of camera 212 is raised, as in camera 212 shown with the symbol (A) in Figure 5, even if chips W1 to W6 are stacked separately in a front pile and a back pile, chips W1 to W4 in the back pile are less likely to be hidden in the shadow of chips W5 and W6 in the front pile. However, if chips W1 to W6 are stacked in a messy, jagged manner, as in camera 212 shown with the symbol (A) in Figure 6, a chip W1 may be hidden in the shadow of another chip W2 above it, or a chip W3 may be hidden in the shadow of other chips W4 and W5 above it, making it difficult to read all of chips W1 to W6.

[0043] Conversely, if the height of camera 212 is lowered, as in camera 212 shown with the symbol (B) in Figure 6, it is easy to read all of chips W1 to W6 even if the chips W1 to W6 are stacked in a messy and jagged manner. However, if chips W1 to W6 are stacked in a pile at the front and a pile at the back, as in camera 212 shown with the symbol (B) in Figure 5, chips W1 and W2 in the pile at the back will tend to be hidden in the shadow of chips W5 and W6 in the pile at the front, making it difficult to read all of chips W1 to W6.

[0044] In addition, even if there is no problem with the way chips W1 to W6 are stacked, if halation (a phenomenon in which external light enters and the image appears white) occurs in camera 212, the contrast of the image will decrease, and the accuracy rate of reading chips W1 to W6 will decrease.

[0045] Conventional AI devices will force an answer (highly likely to be wrong) even for images with low reading accuracy, and because the answer is wrong, the chips bet by customer (player) C will not match the chips in the chip tray. If the game is stopped every time a match does not occur due to a misreading by the AI ​​device, it will be inefficient.

[0046] Taking these points into consideration, the chip judgment device 12 in this embodiment includes, in addition to an artificial intelligence device (artificial intelligence device 12a for chip information judgment) that judges the type and number of stacked chips W, an artificial intelligence device (artificial intelligence device 12b for image pattern recognition) that recognizes image patterns with a low accuracy rate (prone to error).

[0047] The artificial intelligence device 12a for chip information determination performs image analysis on the image of the state of the chips W recorded in the game recording device 11 to determine the number and type of the chips W bet by the customer (player) C. The artificial intelligence device 12a for chip information determination may further determine the position of the chips W bet by the customer (player) C on the betting area BA.

[0048] The artificial intelligence device 12a for chip information judgment performs image analysis of the image of the state of the chips W recorded in the game recorder 11, and determines the state of the chips W in the chip tray 23 before the settlement of each game. The number and type may be determined.

[0049] 3, the tip determination device 12 outputs the determination result to the output device 15. The output device 15 may output the determination result of the tip determination device 12 as character information to a monitor on the gaming table 4, or may output the result as audio information to a headset of the dealer D.

[0050] In addition, the artificial intelligence device 12b for image pattern recognition stores the characteristics of an image of a predetermined state of the chips W, and judges whether the image obtained from the game recording device 11 is an image of the predetermined state. Here, the "image of the chips W in a predetermined state" is an image in which, when the number and type of chips are judged by image analysis of the image, the accuracy of the judgment may be below a certain level, that is, the judgment is doubtful. Specifically, for example, the image includes an image of the chips W1 to W6 piled up in multiple piles taken by the camera 212 at a low position and stored (see the camera 212 indicated by the symbol (B) in FIG. 5), an image of the chips W1 to W6 piled up in a messy and jagged manner taken by the camera 212 at a high position and stored (see the camera 212 indicated by the symbol (A) in FIG. 6), an image in which halation occurs, and the like.

[0051] When the chip determination device 12 judges that the image obtained from the game recording device 11 is an image of a predetermined state by the artificial intelligence device 12b for image pattern recognition, that is, when the chip determination device 12 judges that the level of accuracy of the judgment is below a certain level, the chip determination device 12 outputs a judgment result to the output device 15 indicating that the judgment is unclear.

[0052] In addition, when the chip determination device 12 itself determines that the determination is unclear, it may further have a function of analyzing the image obtained from the game recording device 11 to determine and store whether the cause of the determination of unclear is either (1) the overlapping state of the chips stacked on the gaming table, or (2) a part of or an entire chip W being hidden by another chip.

[0053] With reference to FIG. 5 and FIG. 6, when the chip determination device 12 determines that the image obtained from the camera 212 indicated by the symbol (A) or the camera 212 indicated by the symbol (B) is an image of a predetermined state and is unable to be determined, the chip W may be read using an image captured by another camera 212 indicated by the symbol (C). The chip W can be viewed more objectively by viewing from another angle using a camera in a different direction or at a different position. In particular, when the cause of the determination of indeterminable is that a part or the entire chip W is hidden by another chip as shown in FIG. 5, the chip is not hidden by the other chip by using the camera 212 on the opposite side indicated by the symbol (C). Furthermore, the chip determination device 12 may output the results of reading the chip W using the images captured by each camera 212. In this case, the chip determination device 12 may output the accuracy of the determination of each reading result together, or may consider the result with the largest number of read sheets to be the most likely to be correctly recognized.

[0054] When counting the chips W, the chip determination device 12 may determine that determination is impossible if it recognizes the next chip W without recognizing any chips at a certain vertical interval or more in a group of chips W. In other words, if it recognizes the next chip W without recognizing any chips at a certain vertical interval or more, there is a high possibility that the chips in between are hidden and not visible.

[0055] The tip determination device 12 may be configured to compare the number of tips W determined from the height of the tips W, etc., with the result of determining the type and number of tips W, and output a determination result that the number cannot be determined if the number determination results are different. The number may be determined by determining a specific point (such as the center of the outline of the top tip) from the shape of the tip, and using a method such as triangulation. .

[0056] The judgment correctness determination device 14 is a device that determines whether the judgment result of the chip judgment device 12 is correct or not. The judgment correctness determination device 14 grasps the actual total amount V0 of the chips W in the chip tray 23 when the settlement of the chips bet by the customer (player) C is completed, that is, when the payment to the winning customer (player) C and the collection of the chips W bet by the losing customer (player) C (losing chips) are all completed.

[0057] In this embodiment, the judgment correctness determination device 14 acquires RFID information of the chips W in the chip tray 23 from the RFID reading device 22, and based on the acquired RFID information, determines the type and number of chips W in the chip tray 23 after settlement for each game, and grasps the actual total amount V0.

[0058] The judgment correctness determination device 14 also obtains information on the number and type of chips W as the judgment result from the chip determination device 12, and calculates the total amount of chips W (winning chips) bet by the winning customer (player) C (i.e., the reduction amount of the chip tray 23 in the game) V2 and the total amount of chips W bet by the losing customer (player) C (i.e., the increase amount of the chip tray 23 in the game) V3 based on the obtained chip W information. The judgment correctness determination device 14 then subtracts the reduction amount V2 of the chip tray 23 in the game from the total amount V1 of chips W in the chip tray 23 before settlement of each game, and further adds the increase amount V3 of the chip tray 23 in the game to calculate the total amount of chips that should be in the chip tray 23 V4 (=V1-V2+V3).

[0059] The judgment correctness determination device 14 compares the total amount V4 of the chips W in the chip tray 23 with the actual total amount V0 of the chips W in the chip tray 23, and when there is a difference between the total amount V4 of the chips W in the chip tray 23 and the actual total amount V0 (V4≠V0), it determines that there is an error in the judgment result of the chip judgment device 12. On the other hand, when the total amount V4 of the chips W in the chip tray 23 and the actual total amount V0 match (V4=V0), the judgment correctness determination device 14 determines that the judgment result of the chip judgment device 12 is correct.

[0060] The chip determination device 12 acquires the correctness of the determination result of the chip determination device 12 from the correctness determination device 14. When the correctness determination device 14 determines that the determination result of the chip determination device 12 is correct, the artificial intelligence device 12a for chip information determination learns, as teacher data, the image used in the past (correct) determination when the determination was correct and information on the number and type of chips W as the (correct) determination result. By repeating such learning, the artificial intelligence device 12a for chip information determination can improve the accuracy of determining the number and type of chips W.

[0061] On the other hand, when the judgment correctness judging device 14 judges that the judgment result of the chip judgment device 12 is erroneous, the artificial intelligence device 12b for image pattern recognition learns the image used in the past (incorrect) judgment when the judgment was erroneous as teacher data of the "image of a predetermined state". Images of a predetermined state (an image in which a chip is hidden behind other chips, an image of chips stacked in a jagged shape, an image in which halation occurs, etc.) may be selected by a person and made to learn by the artificial intelligence device 12b for image pattern recognition. Images of a predetermined state (an image in which a chip is hidden behind other chips, an image of chips stacked in a jagged shape, an image in which halation occurs, etc.) may be intentionally created by a person or an artificial intelligence and made to learn by the artificial intelligence device 12b for image pattern recognition. By repeating such learning, the artificial intelligence device 12b for image pattern recognition can accurately extract images that may have a judgment accuracy below a certain level, that is, the accuracy of self-judgment can be improved when self-judging the accuracy of judgment.

[0062] Next, an example of the operation (chip recognition method) of the chip recognition system 10 according to the present embodiment will be described with reference to FIG.

[0063] As shown in FIG. 4, first, when a customer (player) C stacks and places chips W in the betting area BA of the gaming table 4 (the chips W are bet), the game recording device 11 captures and records the state of the stacked chips W as an image using the camera 212 (step S31).

[0064] Next, the tip determination device 12 acquires the image recorded in the game recording device 11. Note that the image acquired by the tip determination device 12 may be selected based on an index, a time, or a tag that identifies a scene of collecting or paying the tip W, which is assigned to the image by the game recording device 11.

[0065] In the tip determination device 12, the artificial intelligence device 12b for image pattern recognition judges whether or not the image obtained from the game recording device 11 is an image of a predetermined state (step S32). More specifically, as described above, the artificial intelligence device 12b for image pattern recognition learns, as teacher data, a plurality of images used in past judgments when the tip determination device 12 made an error in judgment, and as a result of this learning, performs a self-judgment on the accuracy of the judgment of the tip W based on the image in which the judgment result was erroneous, and judges whether or not the accuracy of the judgment falls below a certain level.

[0066] When the artificial intelligence device 12b for image pattern recognition judges that the image obtained from the game recording device 11 is an image of a predetermined state (step S33: YES), the tip determination device 12 outputs a judgment result indicating that the judgment is unclear to the output device 15 (step S40). The judgment result of the tip determination device 12 may be output by the output device 15 to the monitor on the gaming table 4 as character information, or may be output to the headset of the dealer D as audio information.

[0067] On the other hand, if the artificial intelligence device 12b for image pattern recognition determines that the image obtained from the game recording device 11 is not an image of a specified state (step S33: NO), the artificial intelligence device 12a for chip information judgment performs image analysis on the image of the state of the chips W recorded in the game recording device 11 and determines the number and type of chips W bet by the customer (player) C (step S34).

[0068] In addition, in step S34, the chip determination device 12 may perform image analysis of the image of the state of the chips W recorded in the game recording device 11 to determine the number and type of chips W bet by the customer (player) C, as well as the position of the chips W bet by the customer (player) C on the bet area BA, and may also determine the number and type of chips W in the chip tray 23 before settlement of each game.

[0069] Information on the number and type of chips W determined by the chip determination device 12 is output to the output device 15 (step S35). The determination result of the chip determination device 12 may be output by the output device 15 to a monitor on the gaming table 4 as character information, or may be output to a headset of the dealer D as audio information.

[0070] Information on the number and type of chips W determined by the chip determination device 12 is also input to the determination correctness determination device 14. The determination correctness determination device 14 determines whether the determination result of the chip determination device 12 is correct or not (step S36).

[0071] If the judgment correctness determination device 14 judges that the judgment result of the chip judgment device 12 is correct (step S37: YES), the image used for the (correct) judgment by the chip judgment device 12 and information on the number and type of chips W as the (correct) judgment result are input as teaching data to the artificial intelligence device 12a for chip information judgment, and the artificial intelligence device 12a for chip information judgment performs learning (step S38).

[0072] On the other hand, if the judgment correctness determination device 14 judges that the judgment result of the chip judgment device 12 is incorrect (step S37: NO), the image used in the (incorrect) judgment by the chip judgment device 12 is input to the artificial intelligence device 12b for image pattern recognition as training data for an "image of a specified state," and the artificial intelligence device 12b for image pattern recognition performs learning (step S39).

[0073] AI will make big mistakes (confidently give the wrong answer) when there is an error in the judgment result, so by having AI learn image patterns that are easily confused, it can be made to recognize those patterns.

[0074] As described above, according to this embodiment, the chip determination device 12 stores images that reduce the accuracy of reading the chips W as images of a predetermined state, and when it determines that the image obtained from the game recording device 11 is an image of such a predetermined state at the time of determination, it outputs and displays an uncertain determination, rather than forcing an answer. This makes it possible to exclude from the determination results of the number and type of chips W determination results in which a forced answer is given for an image that reduces the accuracy of reading the chips W (i.e., a determination result that is likely to be incorrect). In other words, it becomes possible to determine the number and type of chips W only from images that can be read accurately, and as a result, it becomes possible to recognize the chips W with high accuracy.

[0075] In other words, for example, if the accuracy rate is 99.9% when 1,000 images are judged by the chip judgment device 12, and the accuracy rate is low in 9 out of 10 images with 0.1% errors because the chips are in shadow or the chips are stacked in a jagged manner, the accuracy rate can be increased by another level by excluding such cases from the denominator.

[0076] In addition, according to this embodiment, the image pattern recognition artificial intelligence device 12b can improve the accuracy of its own judgment when it judges the accuracy of the judgment by learning from multiple images used in past (wrong) judgments when there was an error in the judgment as teacher data. This can reduce the situation where an image that can be read correctly is erroneously output and displayed as unclear.

[0077] Furthermore, according to this embodiment, when the chip determination device 12 itself determines that the chip is unclear, it determines and stores whether the cause of the determination is (1) the overlapping state of the chips W stacked on the gaming table 4, or (2) a part or the whole of one chip W is hidden by another chip W, so that the dealer D can easily confirm the cause of the determination of the unclear chip. This allows the dealer D to quickly resolve the cause of the unclear chip by repositioning the chip W in a position where it is not hidden by another chip W, or by neatly stacking the chips W that are stacked in a jagged shape (if the customer (player) C does not like the dealer D touching the chips W, the dealer D may warn the customer (player) C).

[0078] According to the present embodiment, the game recording device 11 adds an index or a time to the image acquired by the camera 212, or a tag that specifies the stacking state of the chips W. Since the chip determination device 12 uses the index, time, and tag assigned to the image to easily identify an image of the state of the chip W to be analyzed from the contents recorded by the game recording device 11, the time required for identification can be shortened.

[0079] In addition, according to this embodiment, the artificial intelligence device 12a for chip information judgment learns from multiple images used in past (correct) judgments when the judgment was correct in the chip judgment device 12 and information on the chip W as the (correct) judgment result as teacher data, thereby improving the judgment accuracy when determining the number and type of chips W.

[0080] The above-described embodiment has been described for the purpose of enabling a person having ordinary skill in the art to practice the present invention. Various modifications of the above-described embodiment are naturally possible for a person skilled in the art, and the technical idea of ​​the present invention can be applied to other embodiments. Therefore, the present invention is not limited to the described embodiment, but should be accorded the broadest scope in accordance with the technical idea defined by the claims.

Claims

1. A chip recognition system for an amusement facility having a gaming table, comprising: The state of the chips stacked on the gaming table is recorded as an image by a camera. A game recording device; A chip determination device, The chip determination device includes: The image of the state of the recorded chips is analyzed to determine the number of chips bet by the player and and a function for determining the type of The image characteristics of a predetermined state of the chips are stored, and the image obtained from the game recorder at the time of judgment is a function of determining whether the image is in the predetermined state; When it is determined that the image obtained from the game recording device is an image of the predetermined state, a judgment is made. A chip recognition system having a function of outputting and displaying the result of the determination that the chip is unknown. Hmm.

2. The chip recognition system according to claim 1, The chip determination device includes an artificial intelligence device, and the artificial intelligence device is When a judgment is made incorrectly at a certain position, multiple images used in past judgments are used as training data. Learn by doing The chip determination device performs a chip determination based on an image in which an error has been detected as a result of the learning. The accuracy of the judgment is judged by the judge, and if there is any doubt about the judgment, it is marked as unclear and the judgment result is recorded accordingly. The chip recognition system further includes a function for outputting and displaying the result.

3. The chip recognition system according to claim 2, When the chip determination device determines that the chip is unclear, the chip determination device analyzes the image of the game recording device. The cause of the indeterminate judgment is the number of chips stacked on the gaming table. The chips are overlapping or partially or entirely covered by other chips. A chip recognition system further having a function of determining and storing which of the above is the cause. Hmm.

4. A chip recognition system according to any one of claims 1 to 3, The game is recorded so that the game record can be later analyzed by the chip determining device. The recording device may provide an index or time stamp to the images captured by the camera, or is a chip recognition system that assigns and records tags that identify the stacking state of chips.

5. A chip recognition system according to any one of claims 1 to 4, The chip judgment device includes a second artificial intelligence device, and the second artificial intelligence device Multiple images and information used in past judgments when the judgment was correct in the chip judgment device A chip recognition system that learns from information on the target and chips using training data.

6. A chip recognition system according to any one of claims 1 to 5, When the chip determination device itself determines that the chip is unclear, it uses a camera other than the camera to determine whether the chip is unclear. and performing image analysis on the recorded image to determine the number and type of chips bet by the player. Chip recognition system.

7. A chip recognition system according to any one of claims 1 to 6, The chip determination device is configured to determine whether or not a chip is detected when the chip is not detected at a certain interval in the vertical direction. If the image is recognized as being in the predetermined state, the image is judged as being in an unclear state and the judgment result is displayed. As the output shows, the chip's recognition system.

8. A chip recognition system according to any one of claims 1 to 7, The chip determination device determines the number of chips based on the height of the chips and the state of the chips. The number of images is compared with the number of images determined by image analysis, and if they are different, the number of images in the predetermined state is The chip recognition system determines that the chip is chip-free and outputs the result as "unknown". Tem.

Images