ROULETTE WHEEL WINNING NUMBER DETECTION METHOD AND APPARATUS

Abstract: A detection system for detecting a winning number in a roulette game played on a roulette wheel having pockets for receiving a ball and having coloured pocket number regions corresponding to the respective pockets, includes a video camera for generating a video image of the roulette wheel including at least one coloured pocket number region and a corresponding pocket. The video data at an array of points in a first fixed area of the colour video image corresponding to a region through which the colour pocket number region will pass are sampled when the cylinder of the roulette wheel is spun. The identity of the coloured pocket number regions are determined from the sampled video data provided by the array of points. The video data is also sampled at a plurality of points in a second fixed area in which the ball can be expected to be when in the pocket corresponding to the identified coloured pocket number region. Whether or not the ball is in the pocket is determined using the sampled video data provided by the plurality of points and the identity of the identified coloured pocket numbered region is output as the winning number if the ball is determined to be in the corresponding pocket.

Description: ROULETTE WHEEL WINNING NUMBER DETECTION METHOD AND APPARATUS The present invention generally relates to a method and apparatus for detecting the winning number in a roulette game. Systems to detect the position of the ball in a roulette wheel are used both to illuminate a display to indicate the winning number to the punters and to collect information for statistical processing. The latter enables the casino to detect that the wheel and its croupier are operating fairly and without bias . In one prior art technique disclosed in WO 95/28996, a detection system is disclosed which uses modulated visible light and analog electronics in order to detect a ball in a pocket and to identify the pocket in which the ball lies. This arrangement suffers from the disadvantage of being difficult to align and inaccurate due to the use of analog electronics in the detection of reflected light. In WO 95/11067, a security system is disclosed in which a video camera is used not only to monitor cheating at the gambling table, but also to detect the winning number by detecting the ball in a pocket of the roulette wheel. This technique suffers from the disadvantage of requiring an image of the whole of the roulette wheel thus requiring the video camera to be mounted above the roulette wheel such as in the ceiling of the casino. Thus apart from the technical difficulties, this is unpopular with casino managers. Further, the technique requires points around the roulette wheel to be determined to generate a linear array. Only a line of points are taken through each pocket number region associated with the pocket and thus this method of identifying pockets in the roulette wheel is prone to error. It is an object of the present invention to overcome the limitations in the prior art and to provide a winning number detection system for a roulette wheel which is accurate and compact. In accordance with one aspect the present invention provides a detection apparatus and method for detecting a winning number in a roulette wheel game in which video images of at least one pocket and at least one corresponding coloured pocket number region in a fifth region of the roulette wheel is obtained. An image of the whole roulette wheel is not required. Thus the video camera used to obtain the video images can be mounted in a more convenient position such as at the side of the roulette wheel. Processing is carried out on an array of points in an area corresponding to a pocket number region in the video image to identify the pocket. The use of an array of points is robust and avoids errors due to reflections from the numbers provided in the pocket number regions and other spurious reflections. Once the pocket number region in the image has been identified, whether or not a ball is present in the corresponding pocket is determined by sampling a number of points in the image in a region in which the ball would be expected to be present. If the ball is detected, the winning number is output as the identified corresponding pocket number region. One aspect of the present invention provides for automatic identification of a first fixed area within the colour pocket number region and a corresponding second fixed area within a corresponding pocket in which the ball can be expected to lie in. The automatic identification of the sampling areas can be achieved in view of the limited field of view over the roulette wheel i.e. the image is of only a section of the roulette wheel. The identification is preferable further simplified by the use of a target which is placed in a predetermined pocket. The target is readily identifiable against the background of the roulette wheel. The location of the target can be carried out using any form of recognition technique e.g. a correlation technique. Once the position of the target has been determined, since the relationship between the pocket and the corresponding coloured pocket number region is known, the search for the sampling area within the coloured pocket number region is simplified i.e. not all of the image need be searched to identify the area. The present invention can be applied to monochromatic images wherein the identities of the pockets can be determined from the intensity of the sampled pixels in the areas: black pocket number regions providing low intensity pixels and red and green pocket number regions providing higher intensity sample pixels. In this monochromatic imaging technique, the green pocket number region can be distinguished from the red pocket number region only by monitoring the sequence of pocket number regions as they pass through the field of view as the roulette wheel is spun i.e. the green pocket lies between a red and black pocket in the single zero roulette wheel and can be detected by detecting two high intensity coloured pocket number regions in succession. The present invention is however more preferably implemented using colour video data from a colour video camera. Using colour video data, the identity of the pockets can be more easily determined by classifying the sample points in the first fixed area into four categories i.e. red, black, green and white. The pixel categorisation at the sample points can simply be determined by the use of thresholds. In one embodiment, the intensity is used to distinguish black and white and a V component calculated in YUV colour space is used to distinguish red and green. The present invention is not however limited to the use of intensity and V values and any single colour coordinates or multiple colour coordinates in any colour space can be used. In a preferred embodiment, a method of identifying the coloured pocket number regions includes determining the colour of each pocket number region as it passes the field of view on the video camera, and comparing the sequence of detected colours with a stored sequence of colour pocket number identities for the roulette wheel. Since the sequence will depend upon the direction in which the roulette wheel is spun, in one embodiment, the direction of rotation of the roulette wheel is also detected to enable the selection of the correct stored sequence of colour pocket number identities to be used in the identification of the coloured pocket number region in the image. When a colour image is provided, and the roulette wheel has a single green zero pocket number region, it is possible to determine the direction of rotation of the roulette wheel by detecting whether the colour transition to the green pocket is from red or from black. Another technique for determining direction which is applicable to monochrome images and to the use with roulette wheels which have a green single zero pocket number region and a green double zero pocket number region comprises comparing sequential video images to identify the direction of movement of an edge of the coloured pocket number region. In one embodiment the identity of the coloured pocket number region is determined using the sample points arranged as a plurality of spaced radial lines in one embodiment. Each line of sample points is used to provide an indication of the identity of the pocket number region. For each sample point a determination is made of the classification of a pixel e.g. red, green, black and white for colour images or black or red/green for monochrome images. An identification for each radial line is obtained by determining which identity is most common to the points along that line. The identity of the coloured pocket number region is then determined as the identity for the majority or a predetermined number of the radial lines of points. In this way each radial line acts as if it were a separate "sensor" and the identity of the coloured pocket number region is determined from the majority or a predetermined number of the "sensors". The identity determined is merely an indication of the colour for the pocket number region and further information e.g. a pocket number sequence, is required in order to identify the pocket number displayed on the pocket number region. Thus this technique of sampling the image in a restricted area provides a fast recognition technique over a 2-dimensional area. The processing carried out by the present invention can either be implemented in specific design hardware, or in a general purpose computer implementing a computer program comprising program routines . The present invention can thus be embodied as a computer program which can be provided on a carrier medium such as a storage medium e.g. floppy disk CD ROMs, programmable memory device, and magnetic tape, and a signal such as an electrical signal carried over a network such as the Internet. Embodiments of the present invention will now be described with reference to the accompanying drawings in which: Figure 1 is a plan view of a roulette wheel showing the detection head of an embodiment of the present invention in position; Figure 2 is a part sectional view of the roulette wheel showing the detection head in position; Figure 3 is a schematic diagram of the components of the detection head; Figure 4 is a circuit diagram of the components of the detection head; Figure 5 is a schematic diagram of a winning number display system in accordance with an embodiment of the present invention; Figure 6 is a schematic diagram of the components of the remote processor in the winning number display system of Figure 5 ; Figure 7 is a flow diagram illustrating the calibration procedure; Figure 8 is a flow diagram illustrating the procedure to determine the fixed sample areas; Figure 9a and 9b illustrate the positioning of the points defining the fixed sample areas determined in the method illustrated in the flow diagram of Figure 8; Figure 9c shows four masks used in the process illustrated in Figures 9a and 9b; Figure 10 is a flow diagram illustrating the process of colour determination of each pixel; Figures 11a and lib are graphs illustrating the method of determination of the thresholds I B I w V G and V R used in the method of Figure 10; Figure 12 is a flow diagram of the method of calculating the detection points in the fixed sample areas; Figure 13 is a diagram illustrating the geometry used in the determination of the points; Figure 14 is a diagram of the layout of the determined points; Figure 15 is a flow diagram of the method of detecting the colour of the coloured number regions; Figures 16a and 16b illustrate the colour determination along radial lines in the sequential images in the section method illustrating in Figure 15; Figure 17 is a flow diagram of the method of determining the identities of the coloured pocket number regions in accordance with an embodiment of the present invention; Figure 18 is a flow diagram of a method of operation of the winning number display system; and Figure 19 is a flow diagram of the method of determining the identities of coloured pocket number regions for a roulette wheel having a green single zero coloured pocket numbered region and a green double zero coloured pocket numbered region. Figure 1 is a plan view of a roulette wheel 1 having a rim 2 onto which is mounted a detector head 3 in accordance with an embodiment of the present invention for detecting the winning number during a roulette game. The roulette wheel has a sloping surface 4 inside the rim 2 which joins the rim 2 at an undercut face 5 around which the ball is spun at the start of the roulette game. This is shown more clearly in Figure 2 which is a part sectional view of the roulette wheel. The detector head 3 is arranged to clamp over the rim 2 of the roulette wheel and includes a sensor for detecting the ball passing in the undercut region 5 of the rim. In this way it can be detected that a ball is in play. The detector head 3 is also provided with a video camera to view a section of the roulette wheel including at least one pocket. The central part of the roulette wheel comprises a cylinder 6 which is rotated during the game whilst the ball is spun around the undercut region 5 of the rim 2. On the cylinder 6 there is provided a sloping face 7. Pockets 8 are arranged in an annulus around the sloping face 7 and coloured pocket number regions 9 associated with the pockets 8 are arranged in an annulus around the pockets 8. As can be seen in more detail in Figure 3 , the detector head 3 contains a circuit board 10 carrying circuit components 11 including a microprocessor. Electrical connections are made via connectors 12 to the circuit board 10. Mounted on the circuit board is a video camera 13 for viewing a section of the roulette wheel. Also, a sensor 14 is provided for detecting the presence of a ball in the undercut region 5 of the rim 2. The sensor 14 is provided in order to detect that the ball is in play and to detect when a ball is about to leave the rim and fall into one of the pockets 8. The components of the detection head 3 will now be described in more detail with reference to the circuit diagram of Figure 4. In this embodiment a colour video camera 13 is provided which has a wide 45 degree field of view. The camera used in this particular embodiment is the colour board camera GP-CX161/45 available from Panasonic . The output from the colour video camera comprises a 768 by 288 pixel field every 20 milliseconds thus providing a 768 by 576 pixel frame every 40 milliseconds. The operation of the video camera 13 can be controlled using a I 2 C control line from a microprocessor 20 provided on the circuit board 10. This allows for the control of parameters such as white balance. As mentioned hereinabove, in addition to providing a video image of a section of the roulette wheel, the detection head 3 is able to detect the ball passing underneath it. The circuitry for achieving this comprises the remaining component of the diagram of Figure 4. The sensor 14 comprises a photodiode 21 for emitting light and a photo-transistor 22 for detecting light reflected by the ball. To drive the photodiode 21 there are provided two transistors 23 and 24. Each of these transistors can provide different driving signal levels by virtue of their connection to the 5 volt supply via resistors 25 and 26. The microprocessor 20 is connected to the transistors 23 and 24 via drive lines and can send modulated driving signals i.e. pulse trains at 1.3 kHz to either one or both of the transistors 23 and 24 to provide an amplitude modulated output from the photodiode 21. If only the transistors 24 is driven, a low drive signal is provided to the phototransistor to generate a modulated output. If the transistor 23 is driven a signal of twice the amplitude is provided to the phototransistor to produce twice the signal level. When the microprocessor outputs the signal to both the transistor 23 and 24, since the outputs are combined, a higher level can be produced. In this way the microprocessor is able to control the output of the photodiode 21 in a binary manner. The level can be set as necessary to ensure that a good signal is received by the phototransistor 22. This will depend upon ambient light conditions and the type of ball used. The signal received by the phototransistor 22 comprises an amplitude modulated signal which is input to an amplifier 27. The output of the amplifier 27 is input directly into the microprocessor 20 to monitor the signal level and ensure that it is not too high or too low. The output of the amplifier 27 is also input into a demodulator 28 for amplitude demodulation to obtain a signal which will be indicative of the passage of a ball 30 passing underneath the sensor 14 and this is input to the microprocessor 20. Within the microprocessor 20, the input signals are digitally converted. The microprocessor used in this embodiment comprises the PIC16C7X 8 bit Cmos microcontroller with A/D converter available from Microchip Technology Inc. The microprocessor 20 is provided with power on 0 and 5 V inputs and includes a communications interface (UART) to a communications line. The output of the microprocessor is a TTL output which includes information identifying when a ball is detected passing underneath the sensor 14. The complete winning number display system will now be described with reference to Figure 5. The detection head 3 outputs video and TTL to a remote processor 40. The remote processor 40 performs the majority of the computation in order to determine the winning number. In particular it performs the video processing as will be described in more detail hereinafter. Winning number information is output over an RS485 line to a controller 50 which is provided with a key pad 51 and is connected to a display 52 which is provided in the vicinity of the roulette wheel for the display of the winning number amongst other information. The remote processor 40 will now be described in more detail with reference to Figure 6. An analog video input is received from the video camera 13 in the detection head 3. This is input to a video digitizer 41 for the digitisation of the analog video and for the subsampling. The analog video is input at a resolution of 768 x 288 pixels per field giving the resolution of 768 x 576 pixels per frame. Each field is subsampled to produce a pixel image of 192 by 144 pixels. A video random access memory (RAM) 42 is provided having two sections FI and F2 to act as ping pong or field switching buffers for receiving sequential subsampled image fields. Thus each section FI and F2 of the video RAM 42 has sufficient memory for storage of 192 x 144 pixels of colour image data. In this way, since each successive field is received 20 milliseconds apart, real time processing on each image field is possible. A processor 43 is provided with flash read only memory (ROM) 44 which contain the computer program code for implementation by the processor 43 and data necessary for the process e.g. the roulette wheel number sequences. The dynamic random access memory (DRAM) 45 is also provided for use by the processor 43 as a working memory. The processor 43 alternately accesses the video RAM 42 in order to read an image field. The processor 43 implements a program written in C. The processor 43 also includes an interface to receive the TTL output from the detection head 3. The processor 43 further includes an RS485 interface to the RS485 line to the controller 50. Thus the processor 43 carries out video processing to identify the winning number, as well as the processing of the TTL signals in order to detect that the ball is in play and to detect when the ball is likely to fall i.e. the point at which no more bets should be placed. The processor 43 is a 32 bit processor. The output information on the RS485 line is in ASCII code and gives a ball in play signal, a no more bets signal, a winning number signal and a game over signal when the ball is removed from the roulette wheel. The processor 43 receives the TTL output of the detection head 3 and detects pulses indicating when a ball passes the detection head 3. In this way when a ball is detected twice indicates that the ball is passing around the rim and thus the game has started. The period between pulses indicates the speed at which the ball is travelling around the rim. The speed at which the ball will leave the rim to fall towards the pocket can be determined and thus when it is detected that the speed of the ball has dropped sufficient such that it will leave the rim shortly, a signal can be generated and output over the RS485 line via the controller 50 to the display 52 to display "NO MORE BETS". This process is incorporated with the winning number detection system as will be described in more detail hereinafter in a complete roulette field gaming system the operation of which will be described in more detail hereinafter with reference to Figure 18. The operation of the system for detecting the winning number will now be described in more detail with reference to Figure 7. This process comprises processing steps carried out by the processor 43. When the detection head 3 is initially placed on a roulette wheel, it is necessary to calibrate the head for accurate detection. This is achieved by placing a marker in the green pocket. This embodiment which comprises the white ball which is placed in the green pocket. The pocket is then aligned with the detection head in step SI to ensure that the pocket and corresponding pocket number region are in the field of view of the video camera 13. The operator can then initiate calibration using an appropriate key on the keypad 51. The controller 50 then sends the "calibrate" instruction to the remote processor 40 and processing of the video data is commenced by the processor 43. The position of the white ball in the video image is detected in step S2 by a correlation technique using a mask as will be described in more detail hereinafter. Once the position of the white ball has been detected, since there is a known relationship between the position of the white ball and the likely area in which the coloured pocket number region lies, in step S3 a search region for the pocket colour identification process is determined. This will be described in more detail hereinafter. Using the position of the white ball ball detection points are calculated in step S4. Also using the determined search region, search line points are determined. These points which lie in two separate areas are used for detecting the presence of a ball in a pocket and for identifying the colour of the pocket number region respectively. Thus the calibration technique automatically and simply identifies regions within the image for the sampling of the pixels to identify the coloured pocket number region and to detect the presence of a ball. The use of the target which is in the form of a white ball in this embodiment greatly reduces the amount of searching required in order to perform the calibration. The details of step S3 in Figure 7 will now be described in more detail with reference to the flow diagram in Figure 8 and the diagrams of Figures 9a and 9b. Figures 9a and 9b represent the image data operated on by the video camera in order to locate coordinates used to determine the regions in which sample points are to be arranged. Figure 9a is a view illustrating points A, B, C, D, E, and F determined by this process. The point X represents the positions of the ball determined in step S2. This position is determined in step S2 using a simple correlation mask to find where coincidence occurs between the while colour mask and the white ball. The mask could be a completely circular one but in practice a semicircular mask may be preferable as in some wheels the ball is partially obscured when located in a pocket. Once the position of the white ball has been determined, the search for the points A, B, C, D identifying the coloured pocket number region will only be carried out below this point i.e. below the line X-X in Figure 9a. This search is carried out using a correlation technique and four masks associated with the points Ab B, C, and D. Thus in step S10 of Figure 8 point A is determined by using a mask in a correlation technique in the region below the ball position. This is illustrated in Figure 9b. The mask will tend to try to move to the corner of the green pocket number region. In step Sll a similar process is carried out to determine point B. In step S12 point C is determined by projecting point B in the X direction to the mid line of the image frame (y-y) and searching downwards by performing a correlation technique using a small square mask. A correlation peak will be detected at the boundary of the green pocket. In step S13 point D is determined by projecting from midway between point A and B in the x direction to the mid y line y-y and searching upwards by forming a correlation technique using a small square mask. Once again a correlation peak will be detected at the green boundary. In step S14 the point F is determined by projecting the ball position to the mid y line y-y. In step S15 the position of point E is determined by projecting from point A upwards along the line AB by the same length as DF. Thus the process performed in the flow diagram of Figure 8 results in the points A, B, C, D, E and F identified in the image as illustrated in Figure 9a. Figure 9c shows a preferred format for the four masks used in identifying the points A, B, C and D which replace the triangular masks shown in Figure 9b. In Figure 9c the masks are rectangular and contain patterns of "GREEN" and "NOT GREEN" with the green patterns indicated by the latched portions. In scale the rectangular masks are preferably at least twice the area of the triangular masks. The process used to determine the position of the white ball comprises the determination of the intensity for all pixels in the image. These have a value between 0 and 255 and they are adjusted to have a value of between -128 and +127. A correlation mask comprising intensity values between -128 and +127 is used to correlate with the image. Where the mask and the white ball overlap a correlation peak is obtained which identifies the ball position. To perform the correlation technique in order to identify the points A, B, C and D, the colour of each of the pixels below the position of the ball is categorised as either black, red, green or white. The process of pixel colour determination will be described in more detail hereinafter. Thus the triangular and square mask used in the process of Figure 8 comprise green masks. The correlation technique is thus a binary correlation technique wherein the number of pixels overlapping of the same colour are counted and the algorithm attempts to keep this to a maximum and to optimise the required coordinates e.g. for point A the y coordinate is minimised and the x is coordinate maximised in order to try to find the top left had corner whilst for the detection of point B, the x and y coordinates are minimised in order to find the bottom left hand corner. The process for determining the colour of the pixels will now be described in more detail with reference to Figures 10 and 11. Figure 10 is a flow diagram illustrating the process of selecting or categorising the colour represented by the pixel. In step S20 the pixel is read. The pixel image data is provided from the digitiser 41 in YUV colour space in this embodiment. The intensity and V component are obtained from the YUV colour space pixel image data from Y and V respectively. In step S21 the intensity I is then compared with a white threshold intensity I w and if it is larger than the white threshold intensity I w , the pixel colour is determined as being white in step S22. If the intensity I is not larger than the white intensity threshold I w in step S23 it is determined whether the intensity I is less than the black intensity threshold I B . If the intensity I is less than the black intensity threshold I B , in step S24 the colour of the pixel is determined as black. If the intensity I is greater than the black intensity threshold I B , in step S25 the V component is compared with a red V component threshold V R . If V component is larger than the red V component threshold V R , in step S26 the pixel colour is determined as red. If the V component is determined not to be larger than the red V component threshold V R in step S27 the V component is compared with the green V component threshold V G . If the V component is less than the green V component threshold V G , in step S28 the pixel colour is determined as green. Otherwise, the pixel colour is undetermined and in step S29 the default colour is set as white . It can be seen from the process of Figure 10 that simple thresholds can be used to categorise pixels into one or four categories: red, green, black or white. When sampling the video image in the coloured pocket number region, not only can black, red and green pixels be identified, but white pixels can be identified because of not only the presence of the highly reflective numbers, but also because of spurius reflections. In order to determine the correct thresholds to be used for colour pixel determination, since the colouring used in roulette wheels can be vary greatly, an embodiment to the present invention allows for automatic determination of the threshold value. This can be achieved by receiving video data when the roulette wheel is spinning. Motion analysis of the video image data enables the identification and elimination of static portions in the image i.e. the non-moving sloping portion of the roulette wheel. Within the moving part of the image, for an image frame, I and V values for each pixel are determined and histograms are generated as illustrated in Figures 11a and lib. As can be seen in these histograms, there is a low intensity peak corresponding to the colour black, a high intensity peak corresponding to reflection from the numbers in the coloured pocket, number regions i.e. white, a low V value peak corresponding to the green pockets, and a high V colour peak corresponding to the red pockets. Thus, the thresholds I B , I w , V G and V R can simply be determined automatically via a suitable relationship with the peaks as illustrated in Figures 11a and lib. The process of determining the colour detection points and the search line points will now be described hereinafter with reference to Figures 12 to 14. In the flow diagram of Figure 12, in step S30, the radius of an arc between each pair of points BC, AD and EF is calculated from the geometry. This is illustrated in more detail in Figure 13. Each pair of points BC, AD and EF can be mapped onto Figure 13 at points x^ and x 2 y 2 • The vertex comprises the mid line y-y and point x 3 y 3 is formed from the mirror symmetrical projection of the point XιY ι . From this geometry the radius is given by the equation below: In step S31, using the determined radius the coordinates for a number n points along an arc from each point x 1 y 1 and x 3 y 3 are determined. In this embodiment n is 11 and there are thus 11 equally spaced points along the arc across the pockets. In step S32 for the n points on the arcs through BC and AB coordinates of m points along a radial line linking each respective pair of n points are determined to determine search line points. In step S33 for each of the n points on the arc through EF, coordinates of a five point array are determined to determine the ball detection points . In this embodiment the five point array comprises an array of five points lying on a cross. The pattern of points is illustrated in Figure 14 and comprises a plurality of ball detection points 60 and an array of pocket colour detection points 61. As can be seen in Figure 14, the ball detection points 60 do not lie directly on the radial projections of the pocket colour detection points 61. The ball detection points 60 are spread along the arc since this has been found to provide better detection. The process of colour detection of the coloured pocket number regions will now be described in more detail with reference to Figures 15, 16a and 16b. In step S40 for each search line the colour of the pixels at each search line point is determined. Pixels for each colour (red, green and black) are counted up for each search line. Since white is not a valid colour determination it is ignored. The colour for each search line is then determined as the colour represented by the majority of the pixels i.e. the colour with the highest count along the search line in step S41. It can thus be seen that in Figure 16a, since all of the search lines lie in the black pocket 31 the colour determination indicated by the square boxes for each search line is black. As can be seen in Figure 16b, both search lines that lie in the red coloured pocket number region 9 are determined as red as indicated in the square boxes. In step S42 the colour of a block of six or more search lines is then determined. In step S43 it is then determined whether the determined colour is different to the previously determined colour determination. If not it is determined that the pocket colour has not changed in step S44. If the colour of the block of six or more search lines is different to the previous determination for the pocket colour, in step S45 it is then determined whether the number of currently determined search lines which are of the previously determined pocket colour are two or more less than in the previous determination: in other words it is determined whether there has been a change of at least two search lines. If so in step S46 the pocket colour is determined as the colour of the block of six or more search lines. If not, in step S44 it is determined that the pocket colour remains unchanged. Thus in step S45 ensures that a change of one search line for example due to "noise" does not result in a change in colour determination for the pocket. This "hysteresis" in the colour pocket number detection makes the colour determination less prone to errors. The process of identifying the number of the pocket using the colour determination will now be described with reference to Figure 17. In step S50 the process determines whether there has been a transition to green detected. If not, the process awaits such a transition. When a transition is detected, in step S51 it is determined whether the counter has reached a predetermined number i.e. whether synchronisation has been detected. The counter is a counter used to count the pockets and thus if the correct number is counted in between detections of green pockets the pocket identification process is in synch. If synchronisation is detected in step S52 it is possible to calculate the speed of rotation of the roulette wheel in revolutions per minute (RPM) . This information is a useful statistic for the remote monitoring of the performance of a croupier. In step S53 the counter can then be cleared. If synchronisation is not detected the process skips step S52 and proceeds straight to step S53 to clear the counter. In step S54 it is then determined whether the transition to green was from red. If so in step S55 it is determined that the direction of rotation of the roulette wheel is clockwise. In step S56 it is then determined whether a transition to black is detected which is the next expected colour. If not this indicates that there is an error and the process returns to step S50 to await for the next transition to green. If the transition to black is detected in step S57 the counter is incremented to indicate the correct count for a pocket and in step S58 the pocket number is determined from the determined direction and the count. The first pocket detected after the green zero will be the black 26 since this is the sequence of numbers. The sequence of numbers is stored for each direction and the count enables identification of the number from either sequence depending upon the direction of rotation. After the detection of the first black pocket in step S58 in step S59 it is then determined whether there has been a transition to red. If not, this indicates an error and the process returns to step S50 to await a transition to green. If a red is detected in step S60 the counter is incremented and in step S51 the pocket number is determined from the determined direction and the count. The pocket number in this case will be number 3. The process can then return to step S56 to sequentially detect the numbers around the roulette wheel. If in step S54 it is determined that the transition is not from red to green, in step S62 it is determined where the transition is from black to green. If not, this indicates that there has been an error and the process returns to step S50 to await the next transition to green. If the transition is from black to green, in step S63 it is determined that the direction is anticlockwise and the process similar to counting in the clockwise direction takes place in the anticlockwise direction starting in step S59. The process of Figure 17 is applicable to a roulette wheel having a single green zero. The operation of the roulette wheel display system during a roulette game will now be described in more detail with reference to Figure 18. In step S70 the process starts and in step S71 the process waits until it is detected that there is no ball in a pocket and there is no ball in the rim. Then in step S72 the process waits until a ball is detected in the rim by the sensor 14. When a ball is detected in the rim, in step S73 the ball's speed is detected and the time predicted to be taken by the ball for the next revolution is determined. If the predicted time as determined in step S74 is less than a threshold, this indicates that the ball will not drop in the next revolution and thus in step S72 the ball is detected in the rim and the ball's speed redetected in step S73. Once it is determined in step S74 that the ball speed is predicted to fall such that the predicted time taken by the ball for the next revolution is above the threshold, in step S75 a "no more bets" signal is transmitted and in step S76 it is determined whether a winning number has been detected i.e. whether a ball has been detected has falling into a pocket. The process waits until the winning number has been detected and once the winning number has been detected in step S77 the winning number is transmitted and the process returns to step S71 to await the removal of the ball so that the game can be played again. The detection of the winning number is based on the detection of a ball in a pocket. The ball is detected using the ball detection points. In order to determine the presence of a white ball, if four out of the five points in a cluster are white, the point is determined as detecting white. When four or more near consecutive points in the arc indicate white detection, it is determined that a ball is present. The embodiment described hereinabove has been described with reference to a roulette wheel having a single green zero pocket. However, roulette wheels are commonly in use which include two diametrically opposed green pockets one being a zero and the other being a double zero. For such a wheel it is not possible to detect the direction of rotation of the wheel by looking at the colour transitions to the green pocket since the green pockets are surrounded by the same colour pockets (the single zero green pocket is surrounded by black pockets and the double zero green pocket is surrounded by red pockets). Thus another technique must be used to determined the direction of rotation. One such technique which can be used is frame comparison. Two successes image fields or frames can be compared to determine the direction of motion by detecting the direction of motion of the edges of the pocket number regions. In addition to the difficulty in detecting the direction of motion, the method of identifying the coloured pocket number regions is also different and will be described hereinafter with reference to Figure 19. In step S80 a transition to green is awaited. When a transition to green is detected in step S81 it is determined whether the counter has reached the end and thus synchronisation is detected. If so, in step S82 the speed of rotation of the roulette wheel can be calculated and in step S83 the counter is cleared. If the counter has not reached its end, it indicates that synchronisation is not achieved and thus the calculation of- the speed rotation of the roulette wheel is skipped and the proceeds to step S83 to clear the counter. In step S84 the direction of rotation is then detected as described hereinabove and in step S85 it is determined whether the transition to green was from red. If so, in step S86 it is determined that the synchronisation pocket is the green double zero pocket. In step S87 it is then determined whether a transition to red is detected. If not, this indicates an error and the process returns to step S80 to await a transition to green. If a transition to red is detected in step S87 the counter is incremented in step S88 and in step S89 the pocket number is determined from the determined direction, the determined synchronisation pocket identity (green double zero) and the count. Then in step S90 it is determined whether the next transition is to black. If not, this indicates an error and the process returns to step S80. If a transition to black is detected in step S90, in step S91 the counter is incremented and in step S92 a pocket number is determined from the determined direction of rotation, the determined synchronisation pocket (green double zero) and the count. The process then returns to step S87 to repeatedly detect red and black coloured pockets. If in step S85 the transition detected is not from red to green, in step S93 it is determined whether the transition is from black to green. If not, this indicates an error and the process returns to step S80. If the transition is detected as being from black to green in step S93, in step S94 the synchronisation pocket is determined as the green zero pocket. In step S90 it is then determined whether the next transition is detected as being to black. If not, this indicates an error and the process returns to step S80. If the transition to black is detected, in step S91 the counter is incremented and in step S92 the pocket number is determined from the determined direction of rotation, the determined synchronisation pocket (the green zero) and the count, the process then proceeds to step S87 and continues as previously described to repeatedly detected red and black pockets. Although the present invention has been described hereinabove with reference to specific embodiments, modifications will be apparent to a skilled person in the art within the spirit and scope of the present invention. For example, although the described technique for determining the areas for the sample points uses correlation techniques, any form of pattern recognition technique can be used. Also, although in the present invention a form of voting is used in the colour determination, any technique can be used for analysing the colours determined at each point in order to decide upon the detected colour. Further, the colour determination technique uses intensity I and the V value. The present invention is not however limited to such colour determination techniques and any colour coordinates can be used in any colour coordinate system. The particular preferred technique of using thresholds in a scalar sequence technique for colour pixels determination can be replaced with a vector comparison in IV space for example or any other colour coordinate space. In the embodiments described hereinabove, during calibration, the white ball is placed in the green pocket and used as a target to determine its position. However, in the french roulette wheel the pockets are deeper and far less of the ball is visible, thus making it more difficult to determine the ball position. It is thus possible to instead use a target placed in the pocket such as a white or blue piece of material which can be easily distinguished over the background colours of the roulette wheel .

Claims: CLAIMS : 1. Detection apparatus for detecting a winning number ' in a roulette game played on a roulette wheel having pockets for receiving a ball and having coloured pocket number regions corresponding to respective pockets, the apparatus comprising: video camera means for generating video data for a video image of said roulette wheel including a region through which said pockets and corresponding coloured pocket number regions pass when a cylinder of the roulette wheel carrying the pockets and coloured pocket number regions is spun; first sampling means for sampling said video data at an array of points in a first fixed area of said video image corresponding to a region through which said coloured pocket number regions will pass when the cylinder of the roulette wheel is spun; identifying means for identifying the coloured pocket number region using sampled video data provided by said array of points; second sampling means for sampling said video data at a plurality of points in a second fixed area of said video image corresponding to a region in which the ball r 37 can be expected to be when in the pocket corresponding to the identified pocket number region; determining means for determining whether the ball is in the pocket corresponding to the identified coloured 5 number region using the sampled video data provided by said plurality of points in said second fixed area; and outputting means for outputting the identity of the identified coloured pocket number region as the winning number if the ball is determined to be in the 10 corresponding pocket. 2. Detection apparatus according to claim 1, wherein said video camera means is adapted to generate colour video data for a colour video image and said identifying 15 means is adapted to determine the colour of said coloured number pocket region in said first fixed area using said sampled video data and to identify the coloured pocket number region using a known sequence of pocket identities . 20 3. Detection apparatus according to claim 1 or claim 2, wherein said video camera means is adapted to generate video data for a video image of only a section of said roulette wheel. 25 4. Detection apparatus according to any preceding claim, wherein said video camera means is adapted for mounting on a rim of said roulette wheel. 5. Detection apparatus according to claim 2, including means for determining the direction of rotation of said cylinders of said roulette wheel, and memory means storing at least one pocket number sequence wherein identifying means is adapted to identify the coloured pocket number region using the determined direction of rotation and a said pocket number sequence read from said memory means by matching the sequence of determined red and black pockets determined after the determination of a green pocket by said first determining means . 6. Detection apparatus according to claim 5, wherein said means for determining direction is adapted to determine the direction of rotation by detecting whether the colour transition to the determination of green by said first determining means is from red or black. 7. Detection apparatus according to any one of claims 1 to 5 , wherein said means for determining is adapded to compare sequential video images to determine the direction of rotation. 8. Detection apparatus according to any preceding claim wherein said first and second sampling means are adapted to sample each image data field of the video data, each video image comprising an image data field. 9. Detection apparatus according to any one of claims 1 to 7 , wherein said first and second sampling means are adapted to sample each image data frame of the video data, each video image comprising an image frame. 10. Detection apparatus according to claim 2, wherein said first sampling means is adapted to use said array of points which are arranged along a plurality of spaced radial lines substantially perpendicular to the expected direction of motion of said coloured pocket number regions in said colour video image, and said identifying means is adapted to determine the colour of a said coloured pocket number region by determining the colour of the image at each point, determining a colour for each radial line points by identifying the colour of each radial line of points which is the most common, and determining the colour of said coloured pocket number region as the colour determined for the majority of the radial lines of points. 11. Detection apparatus according to claim 10, wherein said identifying means is adapted to determine the colour of said coloured pocket number region as the colour determined for a threshold number of the radial lines of points. 12. Detection apparatus according to claim 2, wherein said identifying means and said determining means are adapted to determine the colour of the image at each point as being red, green, black or white by comparing the colour of each pixel of the image at each point with colour threshold values. 13. Detection apparatus according to claim 12, wherein said identifying means and said determining means are adapted to determine the colour of the image at each point by determining the intensity value and the V value YUV colour space for each pixel of the image at each point and comparing the intensity and V values with intensity and V threshold values, black being determined when the intensity value is below an intensity threshold value, red being determined when the V value is above a V threshold value, green being determined when the V value is below a V threshold value, and white being determined when the intensity value is above an intensity threshold value. 14. Detection apparatus according to any preceding claim including a processor and program storage, wherein said first and second sampling means, said determining means, said identifying means and said outputting means comprise computer program routines implemented by said processor and stored as instructions in said program storage. 15. Detection apparatus according to any preceding claim including automatic calibration means for automatically determining said first fixed area in which said array of points is arranged and said second fixed area in which the ball can be expected to be when in the identified pocket by pattern recognition. 16. Detection apparatus according to claim 15, wherein said automatic calibration means includes : means for identifying the position in the video image of a target object placed by a user in a predetermined pocket and positioned in front of said video camera means ; means for searching in a predetermined region of the image relative to the identified position of said target object to identify said first fixed area within the coloured pocket number region corresponding to the predetermined pocket; means for assigning the location of points of said array in the image within said first fixed area within said colour pocket number region; means for identifying said second fixed area in relation to said identified target object position; and second assigning means for assigning the location of points in said image within said second fixed area. 17. Detection apparatus according to claim 16, wherein said means for identifying the position of the target object is adapted to identify the position of the ball as said target object. 18. Detection apparatus according to claim 2, including colour threshold determination means for determining the colour distribution of pixels in an image of the green, red and black coloured pocket number regions, and for determining thresholds to be used in colour determination by said identifying means and said determining means using said colour distribution. r 43 19. Detection apparatus according to any one of claims 15 to 17, wherein said automatic calibration means comprises a processor program routine implemented by a processor. 5 20. Detection apparatus for detecting a winning number in a roulette wheel game played on a roulette wheel having pockets for receiving a ball and having coloured pocket number regions corresponding to respective 10 pockets, the apparatus comprising: a video camera for generating video images of at least one pocket and at least one corresponding coloured pocket number region in a fixed region of the roulette wheel; 15 identifying means for identifying a first fixed area within a coloured pocket numbered region in an image and a corresponding second fixed area in the image within a corresponding pocket in which the ball can be expected to be; 20 video processing means for sampling successive video images within the first and second fixed areas to identify the coloured pocket number regions as they pass said first fixed area in the video images and to identify if a ball is present in the corresponding pocket. 25 21. A method of detecting a winning number in a roulette game played on a roulette wheel having pockets for receiving a ball and having coloured pocket number regions corresponding to respected pockets, the method comprising: receiving video data for a video image of said roulette wheel including a region through which said pockets and corresponding coloured pocket number regions pass when a cylinder of the roulette wheel carrying the pockets and coloured pocket number region is spun; sampling said video data at an array of points in a first fixed area of said video image corresponding to a region through which said coloured pocket number regions will pass when the cylinder of the roulette wheel is spun; identifying the coloured pocket number region using sampled video data provided by said array of points; sampling said video data at a plurality of points in a second fixed area of said video image corresponding to a region in which the ball can be expected to be when in the identified coloured pocket number region; determining whether the ball is in the pocket corresponding to the identified coloured number region using the sampled video data provided by said plurality of points in said second fixed area; and r 45 outputting the identity of the identified coloured pocket numbered region as the winning number if the ball is determined to be in the corresponding pocket. 5 22. A method according to claim 21, wherein colour video data is received for a colour video image, and the step of identifying the coloured pocket number region comprises determining the colour of said coloured number region in said first fixed are using said sampled video 10 data and identifying the coloured number region using a known sequence of pocket identities. 23. A method according to claim 21 or claim 22, wherein the video data received is for a video image of only a 15 section of said roulette wheel. 24. A method according to any one of claims 21 to 23, including the step of determining the direction of rotation of said cylinder of said roulette wheel, wherein 20 the coloured pocket number region is identified using the determined direction of rotation and a pocket number sequence read from memory by matching the sequence of determined red and black pockets determined after the determination of a green pocket . 25 25. A method according to claim 24, wherein the direction of rotation is determined by detecting whether the colour transition to the determination of green is from red or black. 26. A method according to any one of claims 21 to 24, wherein the direction of rotation is determined by comparing sequential video images . 27. A method according to any one of claims 21 to 26, wherein each image data field of the video data is sampled at the points in the first and second fixed areas, and each video image comprises an image data field. 28. A method according to any one of claims 21 to 26, wherein each image data frame of the video data is sampled at each point in said first and second fixed area, and each video image comprises an image frame. 29. A method according to claim 22, wherein said array of points are arranged along a plurality of spaced radial lines substantially perpendicular to the expected direction of motion of said coloured pocket number regions in said colour video image, and the colour of a said coloured pocket number region is determined by determining the colour of the image at each point, determining a colour of each radial line of points by identifying the colour of each radial line of points which is the most common, and determining the colour of the coloured pocket region as the colour determined for the majority of the radial lines of points. 30. A method according to claim 29, wherein the colour of said coloured pocket number region is determined as the colour determined for a threshold number of the radial lines of points. 31. A method according to claim 22, wherein the colour of the image at each point is determined as being red, green, black, or white by comparing the colour of each pixel of the image at each point with colour threshold values . 32. A method according to claim 31, wherein the colour of the image at each point is determined by determining the intensity value and the V value in YUV colour space for each pixel of the image at each point and comparing the intensity and V values with intensity and V threshold values, black being determined when the intensity value r: 48 is below an intensity threshold value, red being determined when the V value is above a V threshold value, green being determined when the V value is below a V threshold value, and white being determined when the 5 intensity value is above an intensity threshold value. 33. A method according to any one of claims 22 to 32, implemented as a computer program by a processor. 10 34. A method according to any one of claims 22 to 33, including the steps of automatically determining said first fixed area in which said array of points is arranged and said second fixed area in which the ball can be expected to be when in the identified pocket by 15 pattern recognition. 35. A method according to claim 33, wherein the automatic determination step includes the steps of: identifying the position in the video image of a 20 target object placed by a user in a predetermined pocket to be visible in the video image; searching in a predetermined region of the image relative to the identified position of said target object to identify said first fixed area within the coloured pocket number region corresponding to the predetermined pocket ; assigning the location of points of said array in the image within said first fixed area within said colour pocket number region; identifying said second fixed area in relation to said identified target object positions; and assigning the location of points in said image within said second fixed area. 36. A method according to claim 35, wherein the position of the ball is identified as the position of said target object when the ball is used as the target object. 37. A method according to claim 22, including the step of determining the colour distribution of pixels in an image of the green, red and black coloured pocket numbered regions, and determining thresholds to be used in colour determination using said colour distribution. 38. A method according to any one of claims 34 to 36, wherein the automatic determination step is carried out by a computer program implemented by a processor. 39. A method of detecting a winning number in a roulette game played on a roulette wheel having pockets for receiving a ball and having coloured pocket number regions corresponding to respective pockets, the method comprising: receiving video images of at least one pocket and at least one corresponding coloured number region in a fixed region of the roulette wheel; identifying a first fixed area within a coloured pocket number region in an image and a corresponding second fixed area within a corresponding pocket in which the ball can be expected to be in the image; sampling successive video images within the first and second fixed areas to identify the coloured number regions as they pass said first fixed area in the video images and to identify if a ball is present in the corresponding pocket; and outputting the identity of the coloured pocket number region when a ball is detected in the corresponding pocket. 40. Processor implementable instructions for controlling a processor to implement the method of any one of claims 21 to 37. 41. A carrier medium carrying the processor implementable instructions of claim 40.

Inventors: PEARCE HENRY COLIN, READ CHRISTOPHER LEWIS, PEARCE, HENRY, COLIN, READ, CHRISTOPHER, LEWIS
Applicants: PEARCE HENRY COLIN, READ CHRISTOPHER LEWIS, TECHNICAL CASINO SERVICES LTD, PEARCE, HENRY, COLIN, READ, CHRISTOPHER, LEWIS, TECHNICAL CASINO SERVICES LTD.
Application year: 2001
Main classification: G07F17
IPC codes: A63F5, A63F9, G07F17