Management System

Abstract

To provide a novel system for detecting fraud in a game in a game parlor or a mistake and fraud when betting chips and settling an amount.SOLUTION: A fraud detection system which detects fraud in a game of performing collection and redemption of chips in accordance with a win or lose result includes: a camera 2 which captures an image of chips 9 contained in a chip tray 17 of a dealer 5; an image analyzing apparatus 12 which analyses the image captured by the camera 2 to detect an amount of the chips 9 contained in the chip tray 17; a card distribution device 13 which determines a win or lose result of a game; and a control device 14 which compares the win or lose result of the game with an amount of the chips 9 contained in the chip tray 17 before and after collection and redemption of the chips to detect fraud.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to a system for detecting fraudulent behavior in games at an amusement arcade, or errors or fraudulent behavior when betting or settling chips. [Background technology]

[0002] Casinos and other gaming establishments are attempting to prevent various types of cheating. Gaming establishments are equipped with surveillance cameras to monitor cheating, and the images captured by the cameras can be used to detect cheating in games and cheating by collecting or redeeming chips that do not correspond to the winning or losing results.

[0003] On the other hand, it has been proposed to attach a radio frequency identification (RFID) tag to each chip to keep track of the number of chips bet and the total amount.

[0004] The card game monitoring system described in Patent Document 1 monitors for fraudulent activity by determining whether chips placed on a gaming table have been collected or redeemed in accordance with the outcome of the game through image analysis of the movement of the chips. [Prior art documents] [Patent documents]

[0005] [Patent Document 1] International Publication No. 2015 / 107902 Summary of the Invention [Problem to be solved by the invention]

[0006] SUMMARY OF THE INVENTION An object of the present invention is to provide a novel system for detecting fraudulent behavior in games at an amusement arcade, or errors or fraudulent behavior when betting or settling chips. [Means for solving the problem]

[0007] One aspect of the present invention provides a cheating detection system for use in an amusement facility having a plurality of gaming tables, the cheating detection system comprising: a game recording device that records the state of a game played at the gaming tables as an image using a camera; an image analyzing device that performs image analysis of the recorded image of the state of the game; a win / loss result determining device that determines the win / loss result of each game at the gaming tables; and a control device that detects cheating at the gaming tables using the image analysis results from the image analyzing device and the win / loss results determined by the win / loss result determining device, and the control device detects cheating at the gaming tables using the position, type, and The total amount of chips in the dealer's chip tray at the gaming table is grasped, and the total amount of chips in the chip tray before settlement of each game is added or subtracted by the increase or decrease in the amount of chips in that game, which is calculated from the positions, types and numbers of chips bet by all players in that game and the win / loss result of that game obtained by the win / loss result determination device, and the total amount of chips that should be in the chip tray after settlement at the end of the game is compared with the actual total amount of chips in the chip tray at the end of the game obtained via the image analysis device, and it is determined whether there is a difference between the total amount that should be and the actual total amount.

[0008] In the above-mentioned fraud detection system, the control device may grasp the position, type and number of chips bet by each player via the image analysis device, and when all of the losing chips bet by each player have been collected, grasp the actual total amount of chips in the chip tray, and compare the total amount of chips that should be in the chip tray, which is calculated by adding the increase in the chip tray amount for that game based on the position, type and number of chips bet by the losing player from the total amount of chips in the chip tray before the settlement of each game, with the actual total amount of chips in the chip tray, and determine whether there is a difference between the total amount that should be and the actual total amount.

[0009] In the above-mentioned fraud detection system, the control device may compare the total amount of chips that should be in the chip tray, calculated by adding the increase in the chip tray amount for that game based on the position, type, and number of chips bet by the losing player to the total amount of chips in the chip tray before the settlement of each game, with the actual total amount of chips in the chip tray, and determine that there is no difference between the total amount that should be and the actual total amount; and may compare the total amount that should be in the chip tray after the settlement at the end of the game with the actual total amount of chips in the chip tray at the end of the game obtained via the image analysis device, and if it determines that there is a difference between the total amount that should be and the actual total amount, it may determine that a payment error has occurred and generate a payment error signal to notify of the payment error.

[0010] In the above-mentioned cheating detection system, the chip tray is provided with a collection chip tray for collecting and temporarily storing chips bet by a losing player, and the image analysis device and the control device may compare the amount of chips that should be in the collection chip tray, calculated from the position, type and number of chips bet by the losing player, with the actual total amount of chips in the collection chip tray, and determine whether there is a difference between the total amount that should be in the collection chip tray and the actual total amount.

[0011] In the above cheating detection system, obtaining the actual total amount of chips in the chip tray after settlement at the end of the game through the image analysis device is: 1) When the redemption of winning chips is completed, 2) When the cards used in the game are collected and discarded in the discard area of ​​the table, 3) When a predetermined button associated with the winning / losing result determination device is pressed, 4) When the marker indicating victory or defeat is replaced.

[0012] In the above-mentioned fraud detection system, when the control device determines that the actual total amount of chips known in the dealer's chip tray at the gaming table does not correspond to the increase or decrease in chips calculated from the amount of chips bet by all players and the outcome of the game, the game recording device may be configured to assign an index or time to the captured video, or to identify and play back the chip collection or payment scene, so that the game recording device can analyze the record of the game in which the difference occurred.

[0013] In the above-mentioned fraud detection system, the image analysis device or control device may be configured to be able to obtain information on the type, number and position of chips bet even if some or all of the chips placed on the gaming table are hidden by the blind spot of the camera.

[0014] In the fraud detection system, the control device 1) The position, type and number of chips bet at each playing position on the gaming table are grasped, and the win / loss history of each player and the amount of chips obtained from the win / loss results of each game are compared with the statistical data of past games to extract peculiar situations; or 2) A situation where the amount of bet chips when losing is smaller than the amount of bet chips when winning at a playing position on a gaming table is extracted as a unique situation by comparing it with statistical data of past games. The structure may be such that

[0015] In the above-mentioned fraud detection system, the control device may be capable of comparing and determining whether the amount of chips known in the dealer's chip tray at the gaming table has increased or decreased in accordance with the payment amount of the chips corresponding to the exchanged bills, or the payment amount of the bills corresponding to the exchanged chips, after the bills have been exchanged for chips.

[0016] In the above-mentioned fraud detection system, the control device may further include a database that records the history of the exchange of bills and chips, and may be able to refer to the database at regular intervals or daily intervals to compare and determine whether the amount of chips recorded in the dealer's chip tray at the gaming table has increased or decreased in accordance with the payment amount of chips corresponding to the exchanged bills, or the total payment amount of bills corresponding to the exchanged chips.

[0017] In the above cheating detection system, the control device may be capable of identifying a player at a playing position extracted as the difference or peculiar situation via the image analysis device.

[0018] In the above-mentioned fraud detection system, the control device may have a warning function that notifies the other gaming table of the presence of the specified player when the specified player leaves his / her seat and takes a seat at the other gaming table.

[0019] In the fraud detection system, the control device further 1) In each game, whether there is any movement of chips between the start of card withdrawal or the start of the game by the dealer and the display of the game result by the card distribution device. 2) After the end of each game, while the dealer is collecting the chips that the loser of the game participants had bet, whether or not the loser has taken any chips; 3) After the end of each game, whether or not chips were added while the dealer was collecting the chips bet by the losing players. 4) After the end of each game, whether the dealer has paid out the winning chips of the players; 5) After each game, whether the winner among the players has taken the chips they bet and the chips they paid; The device may have a function to determine at least one of the above.

[0020] In the above-mentioned fraud detection system, the win / loss result determination device may be a card distribution device that distributes cards at the gaming table, or a control device that determines the win / loss result of each game from information from the image analysis device that reads the cards distributed at the gaming table with a camera. [Effects of the Invention]

[0021] The fraud detection system of the present invention can detect fraud in the collection and redemption of chips according to the outcome of a game.

[0022] Furthermore, with the system of the present invention, even if a player bends a card due to squeezing the card, which is often done in games such as baccarat, the rank and suit of the card can be determined through image analysis, and the total amount of chips can be determined along with their positions, even in blind spots and when chips are overlapped.Fraud when exchanging bills for chips can also be detected. [Brief explanation of the drawings]

[0023] [Figure 1] FIG. 1 is a diagram showing an overview of the entire fraud detection system in an amusement center having a plurality of gaming tables according to a first embodiment of the present invention. [Figure 2A] 2A is a perspective view of a chip showing examples of different stacking states of chips grasped in the first embodiment of the present invention. FIG. [Figure 2B] 2A and 2B are perspective views of chips showing examples of different stacking states of chips grasped in the first embodiment of the present invention. [Figure 3A] FIG. 3A is a diagram showing details of the chip tray according to the first embodiment of the present invention. [Figure 3B] FIG. 3B is a diagram showing another example of the chip tray according to the first embodiment of the present invention. [Figure 4] FIG. 4 is an enlarged view of a mark for explaining stains on a card that are detected in the first embodiment of the present invention. [Figure 5A]FIG. 5A is a plan view showing the front of the marker according to the first embodiment of the present invention. [Figure 5B] FIG. 5B is a plan view showing the back of the marker according to the first embodiment of the present invention. [Figure 6] FIG. 6 is a simplified explanatory diagram showing an image of the exchange state of bills and chips grasped in the first embodiment of the present invention. [Figure 7] FIG. 7 is a plan view showing an overview of a cheating detection system for a baccarat game according to the second embodiment of the present invention. [Figure 8] FIG. 8 is a plan view showing an outline of the progress of a baccarat game in the cheating detection system according to the second embodiment of the present invention. [Figure 9] FIG. 9 is an explanatory diagram showing how the dealer collects chips won by the casino in a baccarat game. [Figure 10] FIG. 10 is an explanatory diagram showing how the dealer pays to winning customers (game players) in a baccarat game according to the second embodiment of the present invention. [Figure 11] FIG. 11 is an explanatory diagram showing how a winning customer (game player) receives chips and payment in a baccarat game according to the second embodiment of the present invention. [Figure 12A] FIG. 12A is an explanatory diagram of an image that is the subject of image analysis when a dealer collects chips that the casino has won in the cheating detection system according to the second embodiment of the present invention. [Figure 12B] FIG. 12B is an explanatory diagram of an image that is the subject of image analysis when the dealer collects chips that the casino has won in the fraud detection system according to the second embodiment of the present invention. [Figure 12C] FIG. 12C is an explanatory diagram of an image that is the subject of image analysis when the dealer collects chips that the casino has won in the cheating detection system according to the second embodiment of the present invention. [Figure 13] FIG. 13 is an explanatory diagram of an image that is the subject of image analysis for fraudulent collection of chips in the fraud detection system according to the second embodiment of the present invention. [Figure 14A]FIG. 14A is an explanatory diagram of an image that is the subject of image analysis for collecting chips won by a game player in the cheating detection system according to the second embodiment of the present invention. [Figure 14B] FIG. 14B is an explanatory diagram of an image that is the target of image analysis for collecting chips won by a game player in the cheating detection system according to the second embodiment of the present invention. [Figure 14C] FIG. 14C is an explanatory diagram of an image that is the target of image analysis for collecting chips won by a game player in the cheating detection system according to the second embodiment of the present invention. [Figure 14D] FIG. 14D is an explanatory diagram of an image that is the subject of image analysis for collecting chips won by a game player in the cheating detection system according to the second embodiment of the present invention. [Figure 15] FIG. 15 is a side cross-sectional view of a card dealing device according to the second embodiment of the present invention. [Figure 16] FIG. 16 is a diagram showing an example of a card according to the second embodiment of the present invention. [Figure 17] FIG. 17 is a plan view of the main part of a card distribution device according to the second embodiment of the present invention, with a card guide part partially cut away. [Figure 18A] FIG. 18A is a side cross-sectional view of a main part showing a distribution limiting device that limits the insertion and removal of cards from a card storage unit of a card distribution device according to a second embodiment of the present invention. [Figure 18B] FIG. 18B is a side cross-sectional view of the essential parts showing a modified example of a distribution limiting device that limits the insertion and removal of cards from the card storage section of the card distribution device according to the second embodiment of the present invention. [Figure 19] FIG. 19 is a diagram showing the relationship between the output waveforms of sensors and marks in the card dealing device according to the second embodiment of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0024] (First embodiment) In gaming facilities such as casinos, chips are placed in high piles on gaming tables, but there is a problem that the IC tag reader installed under the gaming table cannot accurately read the total amount, and if the sensitivity of the reader is increased, chips placed in different positions (where winning or losing depends on the position) will be added up, making it impossible to grasp the total amount of chips at each position.In addition, when capturing images from a camera, there are issues such as blind spots due to the camera's viewing angle, and overlapping chips falling into shadows, making it impossible to grasp the total amount of chips.

[0025] Furthermore, as is often the case in baccarat games, players may squeeze cards (bending face-down cards to look at them little by little while enjoying the card rank, etc.), which can cause the cards to become bent, making it impossible to determine the card rank and suit by analyzing the images from the camera.

[0026] Furthermore, as fraud at gaming tables becomes more sophisticated, new issues have been identified, such as fraud involving sophisticated betting methods that cannot be detected by simply detecting a large amount of winnings at a gaming table, and that cannot be detected by cameras or tracking winning amounts. Furthermore, conventional technology is not sufficient to prevent fraudulent acts involving collusion between dealers and players.

[0027] In order to solve the above-mentioned various problems, the fraud detection system in an amusement facility having a plurality of gaming tables according to the first embodiment includes: A fraud detection system for an amusement facility having a plurality of gaming tables, a game recording device that records the progress of the game played at the gaming table as video images including the dealer and the players via a camera; an image analysis device that performs image analysis on the recorded video of the game progress; a card distribution device that determines and displays the results of each game at the gaming table; and a control device that detects fraudulent behavior at the gaming table using the image analysis results from the image analysis device and the win / loss results determined by the card distribution device.

[0028] Furthermore, in the fraud detection system, the card distribution device is configured to be able to read the rank of the cards being distributed, and the control device is configured to be able to compare the rank information obtained by the image analysis device from the image of each card distributed at the gaming table with the rank information of the cards read by the card distribution device to determine whether they match or not.

[0029] Furthermore, the fraud detection system, in which the image analysis device or control device is an artificial intelligence or deep learning structure that can obtain card ranking information from cards that have been dealt at a gaming table and bent or soiled by a player.

[0030] Furthermore, in the fraud detection system, the control device grasps the position, type, and number of chips bet by each player via the image analysis device, and determines whether the collection of losing chips bet by each player and the payment of winning chips were carried out appropriately in accordance with the outcome of the game by analyzing the video of the game progress via the image analysis device.

[0031] Furthermore, the fraud detection system has an image analysis device or control device that utilizes artificial intelligence or a deep learning structure that can obtain information on the type, number and position of multiple chips bet on the gaming table even if some or all of the chips are hidden by the blind spot of the camera.

[0032] Furthermore, the fraud detection system has an artificial intelligence or deep learning structure in which the control device is capable of comparing and calculating whether the amount of chips known in the dealer's chip tray at the gaming table has increased or decreased in accordance with the recovery of losing chips bet by each player and the amount paid for winning chips after the game ends and settlement, based on the outcome of the game.

[0033] Furthermore, the fraud detection system has an artificial intelligence or deep learning structure in which the control device grasps the position and amount of chips bet at each playing position on the gaming table, and compares the win / loss history of each player and the amount of chips obtained from the win / loss results of each game with statistical data from past games to extract any unusual situations.

[0034] Furthermore, the fraud detection system has a control device that utilizes artificial intelligence or has a deep learning structure that can extract, as an unusual situation when, at a playing position on a certain gaming table, the amount of chips bet when losing is smaller than the amount of chips bet when winning, compared with statistical data from past games.

[0035] Furthermore, in the fraud detection system, the control device is configured to be able to extract the peculiar situation via the image analysis device or to identify individual players at playing positions who have won more than a predetermined amount.

[0036] Furthermore, in the fraud detection system, the control device has a warning function that, when the identified player leaves his / her seat and takes a seat at another gaming table, notifies the other gaming table of the presence of the identified player.

[0037] In order to solve the above-mentioned various problems, the fraud detection system of the present invention for an amusement facility having a plurality of gaming tables comprises: a game recording device that records the progress of the game played at the gaming table as video images including the dealer and the players via a camera; a card distribution device that determines and displays the results of each game at the gaming table; an image analysis device that performs image analysis on the recorded video of the game progress; a control device capable of detecting bills and chips on the gaming table using the image analysis results of the image analysis device; The image analysis device or control device is an artificial intelligence or deep learning structure that can detect, based on information obtained from the card distribution device or the dealer, that an exchange of bills and chips is taking place at the gaming table in a situation other than during card dealing, and can recognize the total amount of genuine bills verified with a black light, and can recognize the total amount of chips even if some or all of the multiple chips placed on the gaming table as exchange targets are hidden by the blind spot of the camera, and can compare the total amount of bills placed on the gaming table by the player with the total amount of chips placed by the dealer and determine whether the amounts match.

[0038] Furthermore, in the fraud detection system, the control device is an artificial intelligence-based or deep learning structure that can perform comparative calculations to determine whether the amount of chips known in the chip tray of the dealer at the gaming table has increased or decreased in accordance with the payment amount of chips corresponding to the exchanged bills after the bills have been exchanged for chips and settlement has been made.

[0039] Furthermore, in the fraud detection system, the control device is an artificial intelligence-utilizing or deep learning structure that can, after the exchange of bills and chips has been completed and settlement has been made, compare and calculate whether the amount of bills deposited by the dealer matches the total amount of bills as determined by the image analysis results of the image analysis device.Furthermore, the control device is an artificial intelligence-utilizing or deep learning structure that can compare and calculate whether the total amount of bills deposited by the dealer at the gaming table that the dealer is in charge of matches the total amount of bills as determined by the image analysis results of the image analysis device.

[0040] According to the fraud detection system of this embodiment, even if a player bends a card by squeezing it, which is often done in games such as baccarat, the rank and suit of the card can be determined through image analysis, and the total amount of chips can be determined along with their positions, even in blind spots and when chips are overlapped.Fraud can also be detected when exchanging bills for chips.

[0041] A first embodiment of the cheating detection system for a gaming parlor with multiple gaming tables according to the present invention will be described in more detail below. FIG. 1 shows the overall system. The cheating detection system for a gaming parlor with multiple gaming tables 4 includes a game recording device 11 that records video of the game progress at each gaming table 4, including the player 6 and the dealer 5, via multiple cameras 2; an image analyzer 12 that analyzes the video of the recorded game progress; and a card dealing device 3 that determines and displays the outcome of each game at each gaming table 4. The card dealing device 3 is a so-called electronic shoe already used by those skilled in the art. It is pre-programmed with the game rules and is designed to read the information on the cards C dealt and determine the outcome of the game. For example, in a baccarat game, whether the banker wins, the player wins, or a tie (draw) is basically determined by the ranks of two or three cards, and the result (win or loss) is displayed by a result indicator lamp 13.

[0042] This cheating detection system further includes a control device 14 that compares the actual card ranks determined by the image analysis device 12 with the win / loss result determined by the card dealing device 3 to detect cheating at the gaming table 4 (such as a discrepancy between the total rank of the dealt cards and the win / loss result). The card dealing device 3 is configured to be able to read the rank (A, 2-10, J, Q, K) and suit (heart, spade, etc.) of cards C manually dealt by the dealer 5, and the control device 14 is configured to compare the rank and suit information obtained by the image analysis device 12 (using artificial intelligence) from images of each card dealt at the gaming table 4 (captured using camera 2) with the card and suit information read by the card dealing device 3 to determine whether they match. The image analysis device 12 and control device 14 in this cheating detection system are configured to be a composite of a computer, program, and memory, which may be an integrated or multiple-component configuration.

[0043] The image analysis device 12 and the control device 14 have an artificial intelligence or deep learning architecture that can obtain card rank information even for cards C dealt at the gaming table 4 that have been bent or soiled by the player 6. As shown in Figure 4, soiled cards C can make it difficult to distinguish between clubs and spades. Even in such cases, the suit can be determined by analyzing and determining the image using an artificial intelligence computer or control system and deep learning (structure) technology. Even if a card is bent due to squeezing by a player, as is often done in games such as baccarat, the suit and rank of the card before deformation can be recognized by the artificial intelligence computer or control system and deep learning (structure) technology, using self-learning of numerous image variations. Since artificial intelligence computer or control system and deep learning (structure) technology are already known and available to those skilled in the art, detailed description will be omitted.

[0044] The control device 14, which utilizes artificial intelligence or a deep learning architecture, can determine, via the camera 2 and the image analyzer 12, where each player 6 bets their chips 9 in the betting area 8 (player, banker, or pair), as well as the type and number of chips 9 (each color of chip 9 is assigned a different value). The chips 9 are stacked in a staggered fashion, as shown in Figure 2A, rather than being aligned vertically. In this case, if the camera 2 is positioned in the direction of arrow X shown in Figure 2A (or if the orientation of the chips 9 is in a blind spot relative to the camera), it is assumed that the chips 9 will not be visible (will be in a blind spot), as shown in Figure 2B. The AI-based computer or control system and deep learning (architecture) technology can use self-learning functions to recognize when chips 9 are hidden by blind spots (when part of a chip is hidden, or when the entire chip is hidden), and accurately determine the number of chips, etc. In this way, it is possible to grasp the position of the chips 9 in the betting area 8 (player, banker, or pair) on which the chips 9 have been bet, the type of chips 9 bet (each color of chips 9 is assigned a different value), and the number of chips 9 bet. Therefore, in accordance with the outcome of each game determined by the card distribution device 3, the control device 14 determines whether the collection of losing chips bet by each player 6 (as shown by arrow L) and the payment of winning chips (9W) to the winning player 6W have been carried out appropriately in accordance with the outcome of the game by analyzing the video of the game progress via the image analysis device 12.

[0045] The control device 14 can analyze and grasp the total amount of chips 9 in the chip tray 17 of the dealer 5 at the gaming table 4 using the image analyzer 12, and after the game is over and settlement is made, it can compare and calculate whether the total amount of chips 9 in the chip tray 17 has increased or decreased according to the outcome of the game, depending on the recovery of the losing chips 9 bet by each player 6 and the amount of winning chips 9W paid to the winning player 6W. Even if the total amount of chips 9 in the chip tray 17 is always grasped by means of RFID or the like, the control device 14 determines whether the increase or decrease is correct by analyzing video of the game progress via the image analyzer 12. These also utilize artificial intelligence or deep learning structures.

[0046] In this example, fraud and mistakes are detected based on the outcome of the game, information on how many of what type of chips 9 were bet and at which position in the betting area 8 (player, banker, or pair), and the increase or decrease in the amount of chips 9 in the chip tray 17 after the losing chips have been collected and the winning chips 9 have been redeemed. Therefore, fraud and mistakes can be detected without knowing the movement of the chips 9 after the game ends, i.e., whether the bet chips 9 have moved to the player's side or the dealer's side.

[0047] Here, in the case of baccarat, for example, the outcome of the game can be determined in accordance with the rules of baccarat by reading the rank of the card C dealt in the game with the card dealing device 3. The outcome of the game can also be determined by taking a picture of the gaming table 4 with the camera 2, analyzing the image with the image analyzer 12, and comparing the analysis results with the game rules with the control device 14. In this case, the camera 2, the image analyzer 12, and the control device 14 constitute a win / loss result determination device. Information regarding the player at each playing position 7, what type of chips 9, and how many chips have been bet on which position (player, banker, or pair) in the betting area 8 is obtained by taking a picture of the chips 9 placed in the betting area 8 with the camera 2 and analyzing the image for each playing position 7 with the image analyzer 12.

[0048] Furthermore, the increase or decrease in the amount of chips 9 in the chip tray 17 before and after the collection of losing chips 9 and the redemption of winning chips 9 can be calculated by comparing the total amount of chips 9 in the chip tray 17 before the collection of losing chips 9 and the redemption of winning chips 9 with the total amount of chips 9 in the chip tray 17 after the collection of losing chips 9 and the redemption of winning chips 9. The total amount of chips 9 in the chip tray 17 before the collection of losing chips 9 and the redemption of winning chips 9 and the total amount of chips 9 in the chip tray 17 after the collection of losing chips 9 and the redemption of winning chips 9 can be detected by photographing the chip tray 17 containing chips 9 with the camera 2 and analyzing the image with the image analyzer 12. Furthermore, the total amount of chips 9 contained in the chip tray 17 may be detected by embedding RFID tags indicating the amount in the chips 9 and providing an RFID reader in the chip tray 17.

[0049] For example, suppose the total value of the chips 9 in the chip tray 17 before the game starts is Bb, and the total value of the chips 9 in the chip tray 17 after the game ends and the collection of lost chips and the redemption of winning chips is Ba. Also, suppose the total value of the chips 9 bet on all playing positions 7 in the player area in this game is bp, the total value of the chips 9 bet on all playing positions 7 in the banker area is bb, and the total value of the chips 9 bet on all playing positions 7 in the tie area is bt. For example, if the banker wins this game, Ba - Bb = bp - bb + bt should be true. Alternatively, the total value of the chips 9 in the chip tray 17 after the game ends should be (Bb + bp - bb + bt). If this is not the case, it can be determined that fraud or an error occurred in the collection or redemption of the chips.

[0050] FIG. 3A shows details of the chip tray of this embodiment, and FIG. 3B shows another example of the chip tray. The chip tray 17 is provided with a collection chip tray 171 that collects and temporarily stores chips 9L bet by the losing player 6L, and a redemption chip tray 172 that stores chips 9W to be redeemed. The image analysis device 12 and the control device 14 grasp the position, type, and number of chips 9L bet by the losing player 6L, and calculate the increase in chips 0L for the game (the amount of chips 9 that should be in the collection chip tray 171). Furthermore, the image analysis device 12 and the control device 14 grasp the actual total amount of chips 9 in the chip tray 171 after collection, and compare the actual total amount with the expected total amount to determine whether there is a difference.

[0051] In addition, by using the chips 9 in the redemption chip tray 172 to redeem the chips 9W for the winning player 6W, sufficient time can be ensured for the image analysis device 12 and the control device 14 to determine the actual total amount of the chips 9 in the collection chip tray 171 after they have been collected.

[0052] The gaming table 4 is provided with a discard area 41 and / or a discard slot 42 for discarding cards C used in a game. Every time a game ends, the cards C used in the game are collected and placed in the discard area 41 or the discard slot 42 on the gaming table 4 to be discarded.

[0053] The gaming table 4 further includes markers 43 that indicate the outcome of the game. FIG. 5A is a plan view showing the front of the marker, and FIG. 5B is a plan view showing the back of the marker. In a baccarat game, two types of markers are used: marker 43a that indicates a player win and marker 43b that indicates a banker win. When the game result is announced, the dealer 5 flips over the marker of either the player or the banker, whichever marker won. This makes the outcome of the game clearly visible on the table. The dealer 5 returns the flipped marker to its original position after the chips 9 have been collected and redeemed. Returning the marker to its original position also indicates that the next game is ready to begin.

[0054] As described above, in this embodiment, the control device 14 calculates the chip balance for each game based on the amount of chips bet on the gaming table 4 and the outcome of the game, and verifies the increase in the chip balance in the chip tray 17 after the game. If the control device 14 detects a discrepancy in this verification, it issues an alarm or adds a note to the video recording taken by the camera 2. The casino operator can investigate the cause of the discrepancy by reviewing the video.

[0055] The fraud detection system of this embodiment adds or subtracts the increase or decrease in the amount of chips in a game calculated from the position, type and number of chips 9 bet by all players 6 in that game and the outcome of the game obtained by the outcome determination device, from the total amount of chips 9 in the chip tray 17 before the settlement of each game, and compares the total amount of chips 9 that should be in the chip tray 17 after the settlement at the end of the game with the actual total amount of chips 9 in the chip tray 17 at the end of the game obtained via the image analysis device 12, and determines whether there is a difference between the total amount that should be and the actual total amount.

[0056] The control device 14 grasps the position, type and number of chips bet by each player via the image analysis device 12, and when all of the losing chips bet by each player have been collected, grasps the actual total amount of chips in the chip tray, and compares the total amount of chips 9 that should be in the chip tray 17, which is calculated by adding the increase in the chip tray 17 for that game based on the position, type and number of chips bet by the losing player from the total amount of chips in the chip tray before the settlement of each game, with the actual total amount of chips 9 in the chip tray 17, and determines whether there is a difference between the total amount that should be and the actual total amount.

[0057] The control device 14 compares the total amount of chips 9 that should be in the chip tray 17, which is the total amount of chips 9 in the chip tray 17 before the settlement of each game, plus the increase in the amount of chips 9 in the chip tray 17 for that game based on the position, type, and number of chips 9 bet by the losing player, with the actual total amount of chips 9 in the chip tray 17, and determines that there is no difference between the total amount that should be and the actual total amount.If the control device 14 compares the total amount that should be in the chip tray 17 after the settlement at the end of the game with the actual total amount of chips 9 in the chip tray 17 at the end of the game obtained via the image analysis device 12, and determines that there is a difference between the total amount that should be and the actual total amount, it determines that there is a payment error and generates a payment error signal to notify of the payment error.

[0058] The chip tray 17 is provided with a collection chip tray 171 for collecting and temporarily storing chips 9 bet by losing players, and the image analysis device 12 compares the total amount of chips 9 that should be in the collection chip tray 171, which is calculated by adding the increase in the amount of chips 9 in the game calculated from the position, type and number of chips 9L bet by the losing player, with the actual total amount of chips 9 in the collection chip tray 171, and determines whether there is a difference between the total amount that should be and the actual total amount.

[0059] When the control device 14 determines that the actual total amount of chips 9 grasped in the chip tray 17 of the dealer 5 at the gaming table 4 does not correspond to the increase or decrease in the amount of chips calculated from the amount of chips bet by all players and the outcome of the game, the game recording device 11 can add an index or time to the captured video, or can identify and play back the scene of collecting or paying out the chips 9, so that the game recording device 11 can analyze the record of the game in which the above-mentioned difference occurred.

[0060] In this way, the control device 14 obtains the total amount of chips in the chip tray 17 after settlement at the end of the game via the image analysis device 12. In this case, the determination after settlement is made when any of the following 1) to 4) occurs. 1) When redemption for the winning chip 9 is completed, 2) When the card C used in the game is collected and discarded in the discard area 41 or discard slot 42 of the table, 3) When a predetermined button attached to the winning / losing result determination device is pressed, 4) When marker 43, which indicates victory or defeat, is returned to its original position.

[0061] The control device 14 is an artificial intelligence or deep learning-based control device that can grasp the position (position bet on player, banker, or pair) and amount (type and number) of chips bet at each playing position 7 of the gaming table 4, and compare the win / loss history of each player 6 and the amount of chips (winning amount) obtained from the win / loss results of each game with statistical data of many past games (big data) to extract peculiar situations (set by the casino). Typically, the control device 14 is an artificial intelligence or deep learning-based control device that can extract peculiar situations such as the occurrence of a winning amount of more than a certain amount (1 million dollars) or a situation in which the amount of chips bet when losing is small and the amount of chips bet when winning is large for several consecutive games at a playing position 7 of a certain gaming table 4, by comparing this with statistical data (big data, etc.) of past games.

[0062] Furthermore, the control device 14 of this fraud detection system (integrated with the image analysis device 12) is configured to be able to identify individual players 6 at playing positions 7 who have been identified as having anomalous circumstances or who have won a predetermined amount or more. To identify such players 6, the image analysis device 12 obtains facial images by extracting feature points or the like, and assigns them an identity number (ID, etc.). The control device 14 has a warning function that, when an identified player 6 leaves his or her seat and takes a seat at another gaming table, notifies the other gaming table of the presence of the identified player. Specifically, the control device 14 notifies the pit manager who manages each gaming table 4 or the person in charge of each table (which may be the dealer) to prevent further anomalous phenomena.

[0063] The control device 14 further has a database that records the history of exchanges of bills K and chips 9, and refers to the database at regular intervals or daily intervals to compare and determine whether the amount of chips 9 held in the chip tray 17 of the dealer 5 at the gaming table 4 has increased or decreased in accordance with the payment amount of chips 9 corresponding to the exchanged bills K, or the total amount of payment of bills K corresponding to the exchanged chips 9.

[0064] In the above example, the win / loss history and the amount of chips (winning amount) obtained for each playing position 7 may be monitored without identifying individual players 6. In this case, if a player 6 leaves his / her seat, that player 6 cannot be tracked. However, it is possible to detect unusual situations, such as a situation where a player at a particular playing position 7 at a single gaming table 4 bets a small amount of chips when he / she loses and a large amount of chips when he / she wins for several consecutive games. If such a playing position 7 is detected, it is possible to suspect that cheating or a mistake has occurred at that playing position 7. Then, by examining the video captured at that playing position 7, cheating or a mistake can be discovered.

[0065] Specifically, the camera 2 is installed so as to capture at least the chips 9 placed in the betting area 8 of the gaming table 4. The image analysis device 12 analyzes the images captured by the camera 2 to detect whether the chips were placed in the player, banker, or tie position in the betting area 8 for each player position 7, and the amount of the placed chips. The card distribution device 3 also functions as a win / loss result determination device, determining the win / loss result of the game. The control device 14 records (monitors) the win / loss history and the amount of chips (chip wins) for each playing position 7 based on the position (player, banker, or tie) in the betting area 8 where the chips 9 were placed and the win / loss result of the game. Note that only either the win / loss history or the chip wins may be recorded. If the win / loss history and / or the chip wins are unusual (as set by the casino) compared with statistical data from a large number of past games (big data), the control device 14 identifies the player position 7 as a playing position suspected of fraudulent activity.

[0066] If cheating is suspected at a certain player position 7, the cheating detection system may emit an alarm (light, sound, or vibration) that can be perceived at least by the dealer at that time. This can at least stop the game from continuing immediately, thereby preventing further cheating. In addition, information indicating that cheating is suspected may be added to the video captured and recorded by camera 2. This allows the cause of the suspected cheating to be investigated by reviewing the video.

[0067] The fraud detection system for a gaming facility having gaming tables in this embodiment also has a function for inspecting the exchange of bills and chips, which is often performed at the gaming table 4. In gaming facilities such as casinos, before a game, a player 6 exchanges bills (cash, etc.) for gaming chips at a designated chip exchange. However, if the player 6 runs out of chips, he or she can continue the game by exchanging cash (bills) for chips 9 at the gaming table (baccarat table, etc.) without leaving the gaming table 4. However, this creates an opportunity for fraud between the dealer 5 and the player. The exchange of cash (bills) for chips 9 at the gaming table (baccarat table, etc.) must be performed when a game is not in progress. The card dealing device 3 is capable of detecting the start and end of card dealing (the time when the win or loss is determined) in order to determine the outcome of the game. For this reason, the card dealing device 3 detects situations other than card dealing (dealing), and the control device 14 detects that bills are being exchanged for chips 9 at the gaming table 4 when cards are not being dealt (as shown in FIG. 6). When cards are being dealt (or other situations), they can be detected based on information obtained from the actions of the card dealing device 3 or the dealer 5.

[0068] The control device 14 can recognize the number and value of bills by performing image analysis of the surface of the bills K. Furthermore, at the gaming table 4, whether the bills K to be exchanged for chips 9 are genuine or not is determined by shining a black light on the bill to detect the authenticity mark G. As shown in FIG. 6, the control device 14 also performs image analysis and verifies the authenticity mark G to recognize the total amount of genuine bills. Furthermore, it can recognize the total amount of chips placed on the gaming table as exchange targets even if they are hidden by the blind spot of the camera 2. It has an artificial intelligence or deep learning structure that can compare the total amount of bills K placed on the gaming table 4 by the player with the total amount of chips 9 placed by the dealer 5 and determine whether the two amounts match.

[0069] The control device 14 has an artificial intelligence or deep learning structure that can perform comparative calculations to determine whether the total amount of chips 9 in the chip tray 17 of the dealer 5 at the gaming table 4 has increased or decreased in accordance with the payment amount of chips corresponding to the exchanged bills after the bills have been exchanged for chips and settlement. The total amount of chips 9 in the chip tray 17 of the dealer 5 may be known in advance at all times using RFID tags or the like on the chips 9. The total amount of chips 9 stored in the chip tray 17 can also be detected by photographing the chip tray 17 containing the chips 9 with the camera 2 and analyzing the image with the image analyzer 12.

[0070] Furthermore, the control device 14 verifies whether the increase or decrease in the amount of chips 9 in the chip tray 17 before and after the exchange of bills for chips matches the exchanged amount of chips as a result of image analysis on the gaming table 4. The amount of the paid bills may be input to the control device 14 by the dealer 5 using a keyboard or the like, or may be determined by taking an image of the gaming table 4 where the bills are paid using the camera 2 and analyzing the image using the image analyzer 12.

[0071] As described above, the control device 14 determines whether the amount of chips 9 deducted from the chip tray 17 due to the exchange of banknotes for chips matches the amount of banknotes paid by the player 6 to the dealer 5. Furthermore, the control device 14 is an intelligent control device that can compare and calculate whether the amount of banknotes deposited by the dealer 5 (usually entered by key input, etc.) matches the calculated amount of banknotes as a result of image analysis by the image analyzer 12 after the exchange of banknotes for chips has been completed and the settlement is complete, and may further be an artificial intelligence-based or deep learning type.

[0072] Furthermore, the control device 14 is an artificial intelligence-based or deep learning structure that can compare and calculate whether the total amount of bills deposited as input by the dealer at the gaming table 4 that the dealer is in charge of matches the total amount of bills as a result of image analysis by the image analysis device 12.

[0073] The control device 14 compares and determines whether the amount of chips 9 grasped in the chip tray 17 of the dealer 5 of the gaming table 4 has increased or decreased according to the payment amount of the chips 9 corresponding to the exchanged banknotes or the payment amount of the banknotes corresponding to the exchanged chips 9 after the exchange of the banknotes and the chips 9.

[0074] (Second embodiment) Baccarat and blackjack are among the many table games played in casinos and other gaming establishments. These games use a standard deck of 52 playing cards, which are dealt onto the gaming table from a card dealing machine that has multiple pre-shuffled decks (6 to 9 or 10 decks). Winning or losing is determined based on the number (rank) of cards dealt and the game rules.

[0075] The dealer in charge of the gaming table handles the distribution of cards from the card distribution device and the settlement of bets made to customers (game participants). Casinos and other gaming establishments attempt to prevent mistakes and fraudulent activities in the settlement of bets made to customers (game participants).

[0076] The card game monitoring system described in International Publication WO2015 / 107902 uses a surveillance camera to read the movement of chips and check whether bets have been paid to winners.

[0077] In baccarat and blackjack, there is a problem in that it is not possible to detect when customers bet or when the dealer settles customers' (game participants') bets, or who placed or took chips, and therefore it is not possible to know whether these are correct.

[0078] In order to solve the above-mentioned various problems, the fraud detection system of the second embodiment is a fraud detection system for an amusement facility having a gaming table, a game monitoring device that uses a camera to monitor the progress of a game played on a gaming table; an image analyzer that analyzes the image obtained by the camera; a card distribution device that determines and displays the results of each game at the gaming table; a control device that uses the analysis results of the image analysis device in each game to identify the positions of chips placed on the gaming table by game participants, and further uses the win / loss results to determine winners and losers among the participants of each game, The control device further 1) In each game, whether there is any movement of chips between the start of card withdrawal or the start of the game by the dealer and the display of the game result by the card distribution device. 2) After the end of each game, while the dealer is collecting the chips bet by the losing players, whether or not anyone other than the dealer has made any chip movements. 3) After the end of each game, whether chips were added while the dealer was collecting the chips bet by the losing players, 4) After the end of each game, whether the dealer has paid out the winning chips of the players; 5) After each game, whether the winner among the players has taken the chips they bet and the chips they paid; and a function of determining at least one of the above.

[0079] Furthermore, the control device may be configured to determine at least one of 1) to 5) by detecting the hand movements, chip movements, or the hand movements and chip movements of the dealer and game participants using the analysis results of the image analysis device.

[0080] Furthermore, the control device may be configured to determine whether the amount of chips paid by the dealer to the winner is correct based on the amount bet by the winner among the players.

[0081] Furthermore, the game cheating detection system may further include a monitor or lamp that issues a warning or display in response to the judgment result.

[0082] According to the fraud detection system of this embodiment, it is possible to detect the timing of bets made by customers and the settlement of bets made by dealers to customers (game participants) in baccarat and blackjack, as well as who placed or took chips, and to detect such mistakes and fraudulent behavior and issue warnings or display messages, leading to the prevention of recurrence.

[0083] Before going into a detailed description of this embodiment, the flow of a baccarat game played in an amusement facility such as a casino will be described. In the second embodiment, the same components as those in the first embodiment will be described with the same numbers.

[0084] As shown in FIG. 7, at a gaming table 4, a customer (game participant / player) 6 sits at a playing position (chair) 7 facing a dealer 5. The customer (game participant) 6 then places chips 9 in a betting area 8 in front of him / her to bet on whether the player or banker will win, or whether the game will end in a tie, as the outcome of the baccarat game (hereinafter referred to as a "bet"). The dealer 5 then waits for the right timing to end the customer (game participant) 6's bet and says "No." In a baccarat game, after "No More Bet" is called and cards are started to be drawn or the dealer 5 operates to start the game, and before the card distribution device 3 displays the results of the game, the customer (game participant) 6 cannot move chips, bet additional chips, or take back chips that have already been bet.

[0085] After that, playing cards 1 are drawn one by one from the card dealing device 3 with their backs facing up onto the gaming table 4. First, four cards are drawn. As shown in circled areas 1 to 4 in FIG. 8, the first card belongs to the player (PLAYER), the second card belongs to the banker (BANKER), the third card belongs to the player (PLAYER), and the fourth card belongs to the banker (BANKER). These cards are then distributed and placed in the area 10 (player area 10P and banker area 10B) in front of the dealer 5 on the gaming table 4. Then, based on the ranks (numbers) of the first through fourth cards 1 and the conditions in the detailed rules of the baccarat game, the dealer 5 draws a fifth card 1 and then a sixth card 1, which become the player (PLAYER) or banker (BANKER) hand. The outcome of the game is then determined based on the ranks (numbers) of the first through fourth cards 1 (and sometimes the fifth and sixth cards as well) and the detailed rules of the baccarat game. Here, the card dealing device 3 is programmed with the rules of the game in advance, and is structured to be able to read the information (rank (number) and suit) of the cards 1 that are dealt and determine the outcome of the game. The outcome (win / loss result) determined by the card dealing device 3 is determined to be consistent with the outcome determined by the dealer or the like as described above.

[0086] The following provides an overview of an embodiment of the cheating detection system for games at amusement parlors according to the present invention. Figure 7 shows an overview of the system. The cheating detection system for games at amusement parlors includes a game recording device 11 that records video of the game progress at a gaming table 4, including the customers (game participants) 6 and the dealer 5, via a camera 2; an image analyzer 12 that analyzes the video of the recorded game progress; and a card dealing device 3 that determines and displays the results of each game at the gaming table 4. The card dealing device 3 is a so-called electronic shoe already used by those skilled in the art. It is pre-programmed with the game rules and is configured to detect when cards 1 are dealt by the dealer 5 at the beginning of each game and read information (rank (number) and suit) of each dealt card 1 to determine the outcome of the game. For example, in a baccarat game, the banker's win, the player's win, and a tie are basically determined by the ranks of two or three cards, and the results (win or loss) are displayed by an indicator lamp 13.

[0087] The control device 14 of this fraud detection system has a chip detection function that uses the analysis results of the image analyzer 12 for each game to determine whether the customer 6 (game participant) bets chips 9 in the player's or banker's betting area 8 on the gaming table 4. It is assumed that the location and total amount of chips 9 (whether the chips 9 are bet in the player's or banker's betting area 8) cannot be read normally, for example, if the chips 9 are misaligned and overlapping or in a blind spot from the camera 2. The control device 14 is configured to recognize chips 9 hidden by blind spots (when part of a chip is hidden, or when the entire chip is hidden) and accurately determine their location, number, etc., using an existing artificial intelligence-based computer or control system, deep learning (structure) technology, or other self-learning function. Furthermore, the structure for detecting the location and type of chips 9 in the betting area 8 is not limited to this; for example, it may be configured to detect them by reading an ID embedded in the chip.

[0088] As explained above, the control device 14 can grasp the position (position where bets are made on player, banker, or pair) and type (different values ​​are assigned to each color of chip 9) and number of chips bet by each player 6 via the camera 2 and image analysis device 12, and can detect which customer 6 bet on player (if there are multiple customers 6 betting on player, which customer 6 bet the most) and which customer 6 bet on banker (if there are multiple customers 6 betting on banker, which customer 6 bet the most). The image analysis device 12 and control device 14 in this fraud detection system have a structure that includes a computer, program, and memory, which may be one or more components.

[0089] The control device 14 is configured to be able to compare the rank and suit information obtained by the image analysis device 12 from the video (using the camera 2) of each card 1 dealt at the gaming table 4 with the rank and suit information read by the card dealing device 3 to determine whether they match. In each game, according to the outcome of the game determined by the card dealing device 3, the control device 14 determines whether the collection of losing chips 9 bet by customers (game participants) 6 and the payment of winning chips to winning customers (game participants) 6 were properly carried out according to the outcome of the game, by analyzing the video of the game progress via the image analysis device 12.

[0090] The control device 14 has the following functions 1) to 5) as characteristic functions of the present invention, and determines whether or not any cheating that violates the rules is occurring in accordance with the rules of the baccarat game. 1) In each game, from the time when the card distributing device 3 sends a signal to start drawing cards, or from the time when the dealer 5 presses the start button 4s to start the game, until the card distributing device 3 displays the result of the game, the image analyzing device 12 uses the camera 2 to monitor whether there is any movement of the chips 9 (as shown in Figure 8). 2) After each game ends, while the dealer 5 is collecting the chips 9 bet by the losers among the game participants 6 (as shown in Figure 9), the image analyzer 12 monitors whether the losers 6 are taking the chips 9 fraudulently, based on information obtained by the camera 2. 3) After each game ends, while the dealer 5 is collecting the chips 9 bet by the losers among the game participants, the image analyzer 12 monitors, using information obtained by the camera 2, whether or not anyone other than the dealer 5 (winner or loser) has added winning chips 9W or placed new chips 9 on the winning side that has not been bet. 4) After each game is over, the image analyzer 12 monitors whether the dealer 5 has correctly placed the payout chip 9W in the position where the winning chip 9 of the game participants 6 had bet (as shown in Figure 10) by using information obtained by the camera 2. 5) After each game is over (the dealer 5 operates the card distribution device 3 to display the winning or losing result on the display lamp 13), the image analysis device 12 uses the camera 2 to monitor whether the winner 6W among the game participants 6 has taken the bet chips 9 and the paid chips 9W (as shown in Figure 11).

[0091] The control device 14 analyzes the information obtained by the image analyzer 12 using the camera 2 as follows. That is, by using the analysis results of the image analyzer 12 to detect the hand movements, chip movements, or the combination of the hand movements and chip movements of the dealer 5 and the game participants 6, it monitors 1) to 5) above, but the basic analysis requires at least knowing who has taken the chips 9. The analysis method will be explained below using Figures 12 to 14.

[0092] Analysis of the fact that Dealer 5 took chip 9 bet by Game Participant 6L (Figure 12). The dealer 5 collects the chips 9 bet by the player 6L who lost the game. Whether or not the chips 9 have been reliably collected is monitored by analyzing information obtained by the image analyzer 12 using the camera 2. First, a change from a state in which the bet chips 9 are present (FIG. 12A) to a state in which they are not present (FIG. 12C) is detected by image analysis. Then, the image (FIG. 12B) between the state in which the chips 9 are present and the state in which they are not present is analyzed. In the image (FIG. 12B) between the state in which the chips 9 are present and the state in which they are not present is analyzed, and the direction from which the hand 5h is extending (from above in FIG. 12 or elsewhere) is analyzed. If the hand 5h is extending from above (or the hand movement is such that the hand appears from above and then recedes above), the hand 5h is determined to be that of the dealer 5. If the hand is extending from any other direction, cheating is detected based on the following rule.

[0093] While the dealer 5 is collecting the chips 9 bet by the player 6L who lost the game, the system monitors whether or not other players are taking the lost chips 9 in an unfair manner (Figs. 12 and 11). In an image that switches between a state in which the chips 9 are present and a state in which they are not present, as shown in Fig. 13, the analysis of whether the loser 6L or other player 6 among the players 6 has taken the chips is performed by detecting through image analysis that a hand 6h extends or moves from below in Fig. 13 (it should actually be from above), and this is determined to mean that a hand 6h other than the dealer 5 is taking the chips 9, and this is determined to be cheating.

[0094] Analysis shows that the dealer 5 correctly paid (placed) chip 9W for the winning chip 9, and that the winning chip 6W among the game participants 6 took it. First, the winning chip 9W shown in FIG. 14A is redeemed in accordance with the game rules, as shown in FIG. 14B. A change from the state shown in FIG. 14A to the state shown in FIG. 14B is detected, and at the same time, image analysis is used to detect whether the hand is the dealer 5's hand 5h. After this, as shown in FIG. 14C, the hand 6h of the winning player 6W among the game participants 6 extends (moves) to the same betting area, and then the control device 14 checks from the image analysis results whether all the chips 9 are lost (the state shown in FIG. 14D) in accordance with the game rules to determine whether there was any cheating.

[0095] Furthermore, the control device 14 is configured to determine whether the amount of chips paid by the dealer 5 to the winner is correct based on the amount bet by the winner 6W among the game participants 6. A specific example is given below. It is assumed that the position and total amount of chips 9 (whether the chips 9 were bet on the player's or banker's betting area 8) cannot be read normally, for example, if the chips 9 are misaligned and overlapping, or if they are in a blind spot from the position of the camera 2. The control device 14 is configured to recognize when chips 9 are hidden by blind spots (when part of a chip is hidden, or when the entire chip is hidden), and accurately determine the position, number, etc., using a self-learning function based on an existing artificial intelligence-based computer or control system or deep learning (structure) technology. Furthermore, the structure for detecting the position 8 and type of chips 9 in the betting area 8 is not limited to this, and may be configured to detect them by reading an ID embedded in the chip, for example.

[0096] As explained above, the control device 14 can grasp the position 8 (position for betting on player, banker, or pair) and type (each color of chip 9 is assigned a different value) and number of chips bet by each player 6 via the camera 2 and image analysis device 12, and can detect which customer 6 bet on the player (if there are multiple customers 6 betting on the player, which customer 6 bet the most) and which customer 6 bet on the banker (if there are multiple customers 6 betting on the banker, which customer 6 bet the most).

[0097] Furthermore, the control device 14 of this cheating detection system for the game analyzes and monitors the information obtained by the image analyzer 12 using the camera 2 in accordance with the rules of the baccarat game using the above-mentioned method. The monitoring described above in 1) to 5) is performed to determine whether any cheating that violates the rules is occurring. When cheating is detected, the card dealing detection device 14C turns on the abnormality indicator lamp 16 provided on both the card dealing device 3 and the gaming table 4, and outputs 15 the detection of cheating to the casino management department or the like via wireless or wired communication. A monitor or lamp that issues a warning or display based on the determination result may also be provided in a separate location.

[0098] As described above, fraudulent behavior is detected by the control device 14, and at the time of detection or at an appropriate time, an indication signal is sent to the indicator lamp 13 or the abnormality indicator lamp 16 of the card distribution device 3. In addition to issuing a warning, the card distribution device 3 may activate its function of preventing card distribution after the time fraud or error is detected, thereby preventing the distribution of card 1.

[0099] An embodiment of the card dealing device 3 used in the table game system of the present invention will be described below with reference to Figures 15 to 19. The card dealing device 3 includes a card storage section 102 that stores a plurality of shuffled playing cards 1s, a card guide section 105 that guides the shuffled playing cards 1 when the dealer 5 or the like manually draws the shuffled playing cards 1 one by one from the card storage section 102 toward the gaming table 4, an opening 106 for removing the cards 1 guided by the card guide section 105, a card detection section (card detection sensors 22 and 23) that detects that the shuffled playing cards 1 have been drawn when the shuffled playing cards 1 are drawn, and a card reading section 10 that reads information indicating at least the number (rank) of the shuffled playing cards 1. 8, a control unit 109 that determines the outcome of the card game based on the number (rank) of shuffled playing cards 1 read in sequence by a card reading unit 108, a result display lamp 13 that displays the outcome determined by the control unit 109, a distribution limiting device 30 that is provided in the opening 106 and limits the entry and exit of cards 1 into the card storage unit 102, and a management control unit 114 that has the same function as the control unit 14, which are integrated together, and have the function of preventing further cards from being drawn from the card distribution device 3 after the control unit 14 detects a dealer's mistake or fraudulent behavior in the game or at a predetermined timing.

[0100] Next, a distribution limiting device 30 that limits the insertion and removal of cards 1 from the card storage unit 102 will be described with reference to Figures 17 and 18. The distribution limiting device 30 is provided in a card guide 107 of a card guide unit 105 that guides cards 1, which are removed one by one from an opening 106 at the front of the card storage unit 102, onto the gaming table 4. The distribution limiting device 30 has a structure in which a locking member 34 presses the card 1 when the card 1 passes through a slot 33 between the card guide unit 105 and a guide cover of the card guide 107, thereby preventing the card 1 from entering or leaving the slot 33. The locking member 34 is moved by a driving unit 35 such as an electromagnetic solenoid or a piezoelectric element, as indicated by arrow m, to take two positions: a position where it presses the card 1 (a limiting position) and a passable position where the card 1 can pass. The drive unit 35 is controlled by a control unit 109 that is directly or indirectly connected to the control device 14 by wire or wirelessly, and moves the lock member 34 to two positions: a position that presses the card 1, and a passable position that allows the card 1 to pass. The rules of the baccarat game are pre-programmed and stored in the control unit 109.

[0101] Next, a modified example of the distribution restriction device 30 will be described with reference to FIG. 18B. In this modified example, the distribution restriction device 40 has a structure in which, when the card 1 passes through the slot 33 between the card guide section 105 and the card guide 107 (guide cover), a locking member 36 protrudes into the slot 33 to prevent the card 1 from moving. The locking member 36 is moved by a driving section 37, such as an electromagnetic solenoid or a piezoelectric element, as indicated by arrow m, so as to be able to take two states: a position that prevents the card 1 from moving (a restricting position) and a passable position that allows the card 1 to pass. The driving section 37 is controlled by a control section 109 connected to the control device 14, and moves the locking member 36 between the position that prevents the card 1 from moving and the passable position that allows the card 1 to pass.

[0102] Next, details of the code reading unit 108, which reads the code 52 representing the number (number, rank) of the card 1 from the card 1 when the card 1 is manually drawn from the card storage unit 102, will be described. FIG. 17 is a plan view of the main parts of the card dealing device 3. In the figure, the code reading unit 108 is provided in a card guide unit 105 that guides the cards 1, which are manually drawn one by one through an opening 106 at the front of the card storage unit 102, onto the gaming table 4. The card guide unit 105 has an inclined surface, and card guides 107, which also serve as sensor covers, are attached to both edges. Each of the two card guides 107 is detachable with screws or the like (not shown). Removing the card guides 107 exposes the sensor group 115 of the code reading unit 108. The sensor group 115 consists of four sensors: two ultraviolet ray reaction sensors (UV sensors) 20 and 21, and object detection sensors 22 and 23.

[0103] The object detection sensors 22 and 23 are optical fiber sensors that detect the presence or absence of the card 1 and can detect the movement of the card 1. The object detection sensor 22 is located upstream of the card guide unit 105 in the direction of card 1 flow, and the other object detection sensor 23 is located downstream. As shown in the figure, the object detection sensors 22 and 23 are located upstream and downstream of the UV sensors 20 and 21. The UV sensors 20 and 21 are equipped with an LED that emits ultraviolet light (ultraviolet LED) and a detector. The card 1 is printed with a mark M of the code 52 using ultraviolet luminescent ink that changes color when exposed to ultraviolet light. The card 1 is irradiated with ultraviolet light (black light), and the reflected light from the mark M of the code 52 on the card 1 is detected by the detector. The UV sensors 20 and 21 are connected to the code reading unit 108 and the control unit 109 via cables. In the code reading unit 108, the combination of the marks M is determined from the output signals of the detectors of the UV sensors 20 and 21, and the number (rank) corresponding to each code 52 is determined.

[0104] In the code reading unit 108, the control unit 109 controls the start and end of reading by the UV sensors 20 and 21 based on the detection signals of the object detection sensors 22 and 23. The control unit 109 also determines whether the card 1 has passed through the card guide unit 105 properly based on the detection signals of the object detection sensors 22 and 23. As shown in FIG. 19 , square marks M representing the rank (number) and suit (e.g., heart, spade) of the card are arranged in two columns and four rows on the edge of the card 1. When the UV sensors 20 and 21 detect the marks M, they output an ON signal. The code reading unit 108 determines the relative relationship between the signals input from the two UV sensors 20 and 21. As a result, the code reading unit 108 identifies the code based on the relative difference between the two marks M detected by the two UV sensors 20 and 21, and identifies the number (rank) and type (suit) of the corresponding card 1.

[0105] The relationship between the code 52 and the ON signal output of the two UV sensors 20, 21 is shown in Figure 19. A specific combination of marks M can be identified based on the comparison results of the relative changes in the ON signal output of the UV sensors 20, 21. As a result, if four combinations of marks M are printed in two upper and lower columns, and four columns are printed, 256 codes can be configured (the fourth power of four). Each of the 52 types of playing cards is assigned to one of the 256 codes, which are stored in memory or a program as a lookup table. The code reader 108 identifies each code 52 and determines the number (rank) and type (suit) of card 1 from a predetermined lookup table (not shown). Furthermore, the 256 codes can be freely associated with the 52 types of cards and stored in the lookup table, allowing for complex combinations and the ability to change the combination of the 256 codes and the 52 types of cards depending on the time and location. The codes are printed with paint that becomes visible when exposed to ultraviolet light, and are preferably printed in a position that does not overlap with the card type markings or the index 103.

[0106] In the above embodiment, the image analysis device 12 and the control device 14 are devices utilizing artificial intelligence or having a deep learning structure. However, the image analysis device 12 and the control device 14 may specifically perform image analysis and the above-mentioned various controls using a scale-invariant feature transform (SIFT) algorithm, a convolutional neural network (CNN), deep learning, machine learning, or similar. These techniques perform image recognition on captured images to recognize objects contained in the images. In particular, deep learning techniques using multi-layered neural networks have been used in recent years to achieve high-accuracy object recognition. This deep learning technique generally achieves high-accuracy object recognition by stacking multiple layers in intermediate layers between the input layer and output layer of a neural network. Among these deep learning techniques, convolutional neural networks in particular have attracted attention for their superior performance in object recognition compared to conventional methods based on image features.

[0107] A convolutional neural network learns labeled target images and recognizes the main object contained in the target image. If there are multiple main objects in the training image, they are designated by a rectangular area, and the image corresponding to the designated area is labeled for training. Furthermore, the convolutional neural network can determine the main object and its location in the image.

[0108] To further explain convolutional neural networks, the target recognition process involves extracting candidate regions based on local features by performing edge extraction or other processing on the image to be recognized, inputting the candidate regions into the convolutional neural network to extract feature vectors and then classifying them, and obtaining the classified candidate region with the highest confidence as the recognition result. Confidence is a quantity that indicates how high the similarity of the subject of an image learned together with a certain image region and label is relative to the similarity of other classes.

[0109] Note that devices utilizing artificial intelligence or having a deep learning structure are described in U.S. Patent No. 9,361,577, U.S. Patent Publication No. 2016-171336, U.S. Patent Publication No. 2015-036920, Japanese Patent Publication No. 2016-110232, etc., and these descriptions are incorporated herein by reference.

[0110] Various embodiments of the present invention have been described above, but it goes without saying that the above-mentioned embodiments can be modified by those skilled in the art within the scope of the present invention, and the device of this embodiment may be appropriately modified according to the needs of the game to which it is applied. [Explanation of symbols]

[0111] 1 Playing Cards 1s Multiple shuffled playing cards 2. Surveillance cameras 3 Card distribution device 4 Gaming Tables 5 Dealer 6 Customers (Game Participants / Players) 7 chairs 8 Betting Area 9 chips 10 areas 10P player area 10B Bunker Area 11 Game Recording Device 12 Image analysis equipment 13 Result display lamp 14 Control device 14C Card distribution detection device 15 Output (abnormality judgment results, etc.) 16. Malfunction indicator lamp 30 Distribution Restriction Device 33 slots 34 Locking member 35 Drive unit 36 Locking member 37 Drive unit 40 Distribution Restriction Device 102 Card storage section 103 Index 105 Card guide part 106 Opening 107 Card Guide 109 Control Unit 112 Side monitor

Claims

1. A management system for managing games played using chips at a gaming table having a plurality of playing positions, a bet chip recognition means for recognizing chips bet on each of the plurality of play positions; where: (1) The bet chip recognition means includes a camera that takes a picture of the chip and generates an image; and an image recognition device that analyzes the image using artificial intelligence or deep learning to recognize the bet chips and determine the number of chips, or (2) The chips are equipped with RFID tags, and the bet chip recognition means is equipped with a reader that recognizes the number of chips by reading the RFID tags built into the chips. a camera that captures images of the plurality of play positions and generates images; a chip operator identification means for analyzing the images generated by photographing the plurality of play positions and identifying the person who operated the chip for each of the plurality of play positions based on the direction of a hand reaching out to the chip placed at the play position and / or the movement of a hand reaching out to the chip at the play position; A management system equipped with

2. The management system according to claim 1 , wherein the chip operator identification means identifies the person who operated the chip by identifying the location of the person who operated the chip.

3. 2. The management system according to claim 1, wherein said chip operator identification means identifies the person who operated each stack for each stack when there are multiple stacks of chips in the same betting area.

4. The management system according to claim 1 , wherein the tip operator identification means identifies the person who took the tip.

5. The management system according to claim 1 , wherein the tip operator identification means identifies the person who placed the tip.

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