Recognition system

Abstract

To provide a recognition system capable of accurately recognizing a plurality of kinds of objects.SOLUTION: A recognition system is a chip recognition system in a game parlor having a game table, and includes a game recording device that records a state of chips stacked on the game table as an image by a camera, and a chip determination device that performs image analysis of the recorded image of the state of the chips and determines the number and type of chips bet by a player. The chip judging device is further provided with a function for storing the feature of the image of the prescribed state of the chip and outputting and displaying that the judgment is unknown as a judged result when it is judged that the image obtained from the game recording device is the image of the prescribed state at the time of judgment.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 that can accurately recognize multiple types of objects.

[0004] The chip recognition system according to the first aspect comprises: A chip recognition system in an amusement facility having a gaming table, comprising: a game recording device that records 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 image of the state of the chips to determine the number and type of chips bet by the player; Equipped with The chip determination device further has a function of storing the characteristics of an image of a chip in a predetermined state, and when it is determined that the image obtained from the game recording device at the time of determination is an image of the predetermined state, outputting and displaying the result of the determination 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 determining that the image obtained from the game recording device is an image of such a predetermined state at the time of determination, it does not force an answer but outputs and displays an uncertain determination to that effect. This makes it possible to exclude from the determination results of the number and type of chips a determination result that is made by forcing an answer based on 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 the 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 there is an error 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 the determination result was incorrect as a result of the learning, and outputting and displaying as the determination result an uncertain determination for images in which there is doubt.

[0007] According to this aspect, the artificial intelligence device of the chip judgment device can improve the accuracy of self-judgment by learning from a plurality of images used in past (incorrect) judgments when there is an error in judgment as training data. This reduces the possibility of an image that can be read correctly being erroneously output and displayed as unclear. It can be done.

[0008] A chip recognition system according to a third aspect is the chip recognition system according to the second aspect, The chip determination device further has a function of, when it determines itself to be an uncertain determination, analyzing the image of the game recording device and determining whether the cause of the uncertain determination is the overlapping state of chips stacked on the gaming table or the state in which part or all of one chip is hidden by another chip, and storing the determined result.

[0009] According to this embodiment, the dealer can easily check the cause of the unclear judgment from the judgment result stored in the chip judgment device. As a result, the dealer can quickly resolve the cause of the unclear judgment by re-placing the chip in a position where it is not shaded by other chips or by neatly stacking chips that are jagged (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 the chip recognition system according to any one of the first to third aspects, The game recording device records the images acquired from the camera by adding an index or time stamp, or a tag that identifies the stacking state of the chips, so that the record of the game can be analyzed later by the chip judgment device.

[0011] According to this aspect, the chip determination 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 the 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, information on a plurality of images and chips used in past judgments when the judgments made by the chip judgment device were correct.

[0013] According to this aspect, 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 when the judgment was correct, 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 the 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 analyzes images 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 the 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 predetermined 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 the determination result as unclear.

[0017] A recognition system according to a ninth aspect includes: A recognition system in which a determination object has a plurality of types and the object is distinguished by type to determine the number of each type, 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 of 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 training data, and has the function of self-judging the accuracy of the judgment.If the level of accuracy is below a certain level, it will self-judgment that the judgment result is doubtful, and further has the function of outputting and displaying the judgment result as unclear.

[0018] According to this aspect, the determination device learns from past determination results as training data, and for a new image, first, it self-determines the accuracy of the determination, and if the level of accuracy is below a certain level, 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 of each type of object a determination result that is made when a forced answer is given for an image that has low accuracy in the determination (i.e., a determination result that is likely to be incorrect). In other words, it becomes possible to determine the number of each type of object only from images that can be accurately read, and as a result, it becomes possible to recognize objects with high accuracy. [Brief explanation of the drawings]

[0019] [Figure 1] FIG. 1 is a diagram schematically showing an amusement center equipped with a chip recognition system according to one embodiment. [Figure 2] FIG. 2 is a diagram for explaining the progress of a baccarat game. [Figure 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 illustrating a chip recognition method according to an embodiment. [Figure 5] FIG. 5 is a diagram for explaining a case where one chip is hidden behind another chip. [Figure 6] FIG. 6 is a diagram for explaining the case where chips are stacked in a jagged manner. DETAILED DESCRIPTION OF THE INVENTION

[0020] Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings. In each drawing, components having equivalent functions are designated 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 recognition system for chips in an amusement arcade with gaming tables will be described as an example of a recognition system that distinguishes objects by type and determines the number of each type, but it goes without saying that the object to be determined is not limited to chips as long as it has multiple types.

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

[0023] FIG. 1 is a diagram schematically illustrating an amusement facility equipped with a chip recognition system 10 according to one embodiment. As shown in FIG. 1, the amusement 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 the dealer D. The number of chairs 201 is arbitrary, and in the example shown in FIG. 1, six chairs 201 are arranged. In addition, a betting area BA is provided on the gaming table 4 corresponding to each chair 201. That is, in the example shown, six betting areas BA are arranged in an arc shape.

[0024] As shown in Fig. 1, customers (players) C are seated at each of the chairs 201. Customers (players) C bet on the outcome of the baccarat game, whether the player or the banker will win, or whether the game will end in a draw (TIE), by placing chips W in a pile on a betting area BA in front of the chairs 201 where they are seated (hereinafter, this will be referred to as a "bet").

[0025] The chips W to be bet may be of one type only, or may be of 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] 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 card shooter device S onto 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, the drawing of the first to fourth cards will be referred to as "dealing").

[0027] All cards are drawn face down from the card shooter S. 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 bet the highest amount; if there are no customers who bet on PLAYER, the dealer D) turns the first and third cards, which were 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 bet the highest amount; if there are no customers who bet on BANKER, the dealer D) turns the second and fourth cards face up (this turning face down cards face up is generally called a "squeeze").

[0029] Then, based on the ranks (numbers) of the first four cards and the detailed rules of the baccarat game, dealer D draws a fifth card and then a sixth card, which become the hand of the player or banker, respectively. Similarly, customer (player) C, who bet on the player, squeezes the cards that will become the player's hand, and customer (player) who bet on the banker squeezes the cards that will become 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 be known 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 finally decide the winner. Dealer D determines that the winner has been decided and the result of the game 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 customer (player) C.

[0032] At the same time, the outcome of the game is determined by a win / loss determination unit possessed by the card shooter device S. If the dealer D attempts to draw another card without displaying the outcome of the game even though the outcome has been decided, this is an error. The card shooter device S detects the error and outputs an error signal. Finally, while the outcome of the game is being displayed, the dealer D settles the chips bet by the customer (player) C, paying the winning customer (player) C and collecting the chips bet by the losing customer (player) C. After the settlement is complete, the display of the outcome of the game is terminated and betting for the next game begins.

[0033] The above-described flow of a baccarat game is widely practiced in ordinary 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 result display unit, and is equipped with the function of determining whether or not a player has won or lost and displaying the results of the win or loss. On an ordinary casino floor, a card shooter device S and a monitor are placed at each of the multiple gaming tables 4 lined up, and the cards to be used are supplied in packages, sets, or even cartons to each gaming table 4 or to the cabinet below it.

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

[0035] 1, in this embodiment, a monitoring camera 212 that captures images of the chips W stacked and arranged in the betting area BA is provided outside the gaming table 4. In addition, 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 that reads the RFID of the chips W in the chip tray 23.

[0036] The chip recognition system 10 according to this embodiment is communicably 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 determination device 12, and a determination correctness determination 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 gaming 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 acquired from the camera 212 so that the game record can be later analyzed by the chip judgement device 12, which will be described later. Alternatively, a tag specifying the scene of collecting or paying the tip W may be attached 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, jagged manner (see Figure 6), the camera 212 cannot see the entire chips W1 to W6, which may result in a lower accuracy in reading the chips W1 to W6.

[0042] More specifically, if the height of camera 212 is raised, as in camera 212 indicated by 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 indicated by the symbol (A) in Figure 6, a certain chip W1 may be hidden in the shadow of another chip W2 above it, or a certain 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 indicated by the symbol (B) in Figure 6, it is easy to read all of chips W1 to W6 even if they are stacked in a messy and jagged manner. However, if chips W1 to W6 are stacked in separate piles in the front and back, as in camera 212 indicated by the symbol (B) in Figure 5, chips W1 and W2 in the back pile will likely be hidden in the shadow of chips W5 and W6 in the front pile, making it difficult to read all of chips W1 to W6.

[0044] Furthermore, 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 (with a high probability of being 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 determination device 12 in this embodiment includes, in addition to an artificial intelligence device (artificial intelligence device 12a for chip information determination) that determines 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 mistakes).

[0047] The artificial intelligence device 12a for determining chip information analyzes 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 artificial intelligence device 12a for determining chip information may further determine the position of the chips W bet by the customer (player) C on the betting area BA.

[0048] The chip information determination artificial intelligence device 12a performs image analysis on the images of the state of the chips W recorded in the game recording device 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 also 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 it as audio information to a headset of the dealer D, etc.

[0050] Furthermore, the image pattern recognition artificial intelligence device 12b stores the characteristics of images of chips W in a predetermined state, and determines whether the image obtained from the game recording device 11 is an image of the predetermined state. Here, an "image of chips W in a predetermined state" is an image in which, when the image is analyzed to determine the number and type of chips, the accuracy of the determination may be below a certain level, i.e., an image in which the determination is questionable. Specifically, for example, an image of chips W1 to W6 stacked in multiple piles taken and stored by a camera 212 positioned low (see the camera 212 indicated by the symbol (B) in FIG. 5), an image of chips W1 to W6 stacked in a messy, jagged manner taken and stored by a camera 212 positioned high (see the camera 212 indicated by the symbol (A) in FIG. 6), an image in which halation occurs, etc.

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

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

[0053] 5 and 6, if 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 therefore indeterminable, it may read the chip W using an image captured by another camera 212 indicated by the symbol (C). The chip W can be viewed more objectively by viewing from a different angle using a camera oriented or positioned in a different direction. In particular, if the cause of the determination of indeterminable is that part or all of the chip W is obscured by another chip, as shown in FIG. 5, the opposite camera 212 indicated by the symbol (C) can be used to ensure that the chip is not obscured by the other chip. 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 the result with the most number of reads may be considered to be the most likely to be correctly recognized.

[0054] When counting 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 the 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, it is highly likely that the chips in between are hidden and not visible.

[0055] The chip determination device 12 may be configured to compare the number of chips W determined from the height of the chips W, etc., with the result of determining the type and number of chips W, and if the number determination result differs, output a determination result that the determination is impossible. The number may also be determined by determining a specific point (such as the center of the outline of the top chip) from the shape of the chips 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 determination 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 of each game, and grasps the actual total amount V0.

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

[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 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 matches the actual total amount V0 (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 determination correctness determination device 14. If the determination 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 training 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 this 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, if the judgment accuracy determination device 14 determines 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 previous (incorrect) judgment when the judgment was erroneous as training data for "images in a predetermined state." Images in a predetermined state (such as an image in which one chip is hidden behind another, an image of chips stacked in a jagged pattern, or an image with halation) may be selected by a person and trained by the artificial intelligence device 12b for image pattern recognition. Images in a predetermined state (such as an image in which one chip is hidden behind another, an image of chips stacked in a jagged pattern, or an image with halation) may be intentionally created by a person or an artificial intelligence and trained by the artificial intelligence device 12b for image pattern recognition. By repeating this type of learning, the artificial intelligence device 12b for image pattern recognition can accurately extract images for which the accuracy of judgment may be below a certain level, i.e., the accuracy of self-judgment can be improved when self-judging the accuracy of judgment.

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

[0063] As shown in FIG. 4, first, when a customer (player) C places chips W in a stack 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 judgment 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 training data, a plurality of images used in past judgments when the tip judgment device 12 made an error in judgment, and as a result of this learning, makes a self-judgment on the accuracy of the judgment of the chip W based on the image in which the judgment result was erroneous, and judges whether or not the accuracy of the judgment is below a certain level.

[0066] When the image pattern recognition artificial intelligence device 12b 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 text information, or may be output as audio information to the headset of the dealer D, etc.

[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 predetermined state (step S33: NO), 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 and determines the number and type of chips W bet by the customer (player) C (step S34).

[0068] In step S34, the chip determination device 12 may perform 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, as well as the position of the chips W bet by the customer (player) C on the betting area BA, or may 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 text information, or may be output as audio information to a headset of the dealer D, etc.

[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 determines 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 the information on the number and type of chips W as the (correct) judgment result are input as training 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 determines that the judgment result of the chip judgment device 12 was 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 the "image of a specified state," and the artificial intelligence device 12b for image pattern recognition performs learning (step S39).

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

[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 that are made by forcing an answer based on 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] 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 because 9 out of 10 images have a chip in shadow or the chips are stacked in a jagged manner, the accuracy rate can be raised by another level by excluding such cases from the denominator.

[0076] Furthermore, according to this embodiment, the artificial intelligence device 12b for image pattern recognition can improve the accuracy of its own judgment when it judges the accuracy of its own judgment by learning from multiple images used in past (incorrect) judgments when there is an error in judgment, thereby reducing the number of cases where an image that can actually be read accurately is erroneously output and displayed as unclear.

[0077] Furthermore, according to this embodiment, when the chip determination device 12 itself determines that the determination is unclear, it determines and stores whether the cause of the determination is (1) whether the chips W stacked on the gaming table 4 are overlapping, or (2) whether a part of or the entire chip W is hidden by another chip W, so that the dealer D can easily confirm the cause of the determination of unclear. This allows the dealer D to quickly resolve the cause of the unclear determination 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 jagged (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] Furthermore, according to this embodiment, the game recording device 11 assigns an index or a time to the image acquired from 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, it can easily identify the image of the state of the chip W to be analyzed from the recorded contents of the game recording device 11, thereby reducing the time required for identification.

[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 in the chip judgment device 12 was correct and information on the chip W as the (correct) judgment result as training data, thereby improving the accuracy of judgment when determining the number and type of chips W.

[0080] The above-described embodiments have 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 embodiments would naturally be possible for a person skilled in the art, and the technical concept of the present invention may also be applied to other embodiments. Therefore, the present invention is not limited to the described embodiments, but should be accorded the broadest scope in accordance with the technical concept defined by the claims.

Claims

1. A chip recognition system in an amusement facility having a gaming table, comprising: a game recording device that records 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 image of the state of the chips to determine the number and type of chips bet by the player; Equipped with The chip recognition system further includes a function in which the chip determination device stores the characteristics of an image of a chip in a predetermined state, and when it determines that the image obtained from the game recording device at the time of determination is an image of the predetermined state, outputs and displays the determination as unclear as a determination result.

2. The chip recognition system according to claim 1, The chip determination device includes an artificial intelligence device, and the artificial intelligence device learns a plurality of images used in past determinations when there is an error in the chip determination device as training data, The chip recognition system further includes a function in which the chip judgment device judges the accuracy of the judgment itself based on images in which an error in the judgment result was found as a result of the learning, and outputs and displays the judgment result as unclear for images in which there is doubt about the judgment.

3. The chip recognition system according to claim 2, The chip recognition system further comprises a function of analyzing the image of the game recording device when the chip determination device itself determines that the determination is unclear, and determining and storing whether the cause of the determination that the determination is unclear is that the chips are stacked on the gaming table in an overlapping state, or that part of or the entire chip is hidden by another chip.

4. 4. A chip recognition system according to claim 1, A chip recognition system in which the game recording device records images acquired from a camera by assigning an index or time stamp, or a tag that identifies the stacking state of the chips, so that the game record can be later analyzed by the chip judgment device.

5. A chip recognition system according to any one of claims 1 to 4, A chip recognition system in which the chip judgment device includes a second artificial intelligence device, and the second artificial intelligence device learns, as training data, multiple images and chip information used in past judgments when the judgment in the chip judgment device was correct.

6. 6. A chip recognition system according to claim 1, The chip recognition system is configured such that, if the chip determination device itself determines that the chip is unclear, it analyzes images recorded by a camera other than the camera to determine the number and type of chips bet by the player.

7. 7. A chip recognition system according to claim 1, The chip recognition system is such that, if the chip determination device recognizes the next chip without recognizing a chip at a certain interval 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.

8. A chip recognition system according to any one of claims 1 to 7, The chip determination device compares the number of chips determined from the height of the chips with the number determined by image analysis of the image of the state of the chips, and if they differ, determines the number of chips determined from the image of the predetermined state. A chip recognition system that determines that there is a chip and outputs and displays the result as unclear.

9. A recognition system in which a determination object has a plurality of types and the object is distinguished by type to determine the number of each type, 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 of 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, has a function of self-judging the accuracy of the judgment, and if the level of accuracy is below a certain level, self-judges that the judgment result is doubtful, and further has a function of outputting and displaying the judgment result as unclear.

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