💰 BlackJack Code by Stanley Brown on Prezi Next

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Unfortunately, we never got our camera working. PCLK relates to pixel timing. This became problematic as many characters in the rank of the card have similar pixel ratios there was also a degree of variability due to each picture. We chose this because we set up the camera for QCIF format which is x both numbers are divisible by 4. The sixth image shows the cropped rank. Next, it applies thresholding to turn the picture into a binary black and white image. Once the image is in the proper format, the characters making up the rank and suit of the card is extracted. As soon as it sends this signal, Matlab runs fscanf to scan the port. Then, to randomly pick a card, we chose a random file and ran the image reconition algorithm on that file. As each line was drawn, it observed any variation in color. Most characters had a unique signature. Therefore, the problem either came from not setting the control registers correctly or not understanding how the data was output. The fourth is resized. We also added double down as an option where the player bets twice as much but only gets to hit once. Therefore, in this case, rank and suit was given the Ace of Spades. These registers are enumerated in the data sheet. This made it impossible to crop the image to extract the characters. Below are 10 pictures demonstrating the image processing and recognition process. The reason is that the human eye is much more sensitive to intensity Y then color. Similarly 6, 9, and the Queen required another handler to distinct the three. Thus, the initial design we present is without a camera. Instead, to determine rank, 4 lines were drawn across the image. First, it was used to do image processing and recognition. The start of data transmission is signalled by SIOD being pulled from a floating tri-state to low. The tenth image is the cropped suit. However, 3 and 5 required a special handler to determine where their upper half of the character lies. Camera write is achieved by sending the start signal which includes the 'write' register 0x42 in this case followed by the register we are writing to followed by the data. We keep track of who has an ace with a boolean variable. However, we were never able to get the camera fully functional. The suit was determined by cropping the suit character and performing a pixel ratio test. The second is the threshold. If it receives "irq", it knows that the MCU needs data either the player's bet or the player's move. Then, it would send the data to Matlab which would do image processing and recognition. HREF is low between the last byte and the first byte of a new line. The white space to the left, right, top, and bottom of the image is removed. HREF going high signals the start of a new line. HREF corresponds to horizontal lines. The seventh image shows how we get the suit note that it is the box below the rank box. The image is then trimmed on top and bottom until its height and width are in the x ratio. This option is removed from the state diagram for the purpose of clarity. The blackjack algorithm is straightforward as far as blackjack algorithms go. This way, we demonstrated that we understood how to do image recognition. In YUV, 2 bytes form 1 pixel and 4 bytes form a macropixel. By marking the amount of color variations for each line, a "signature" of the rank could be determined.

We initially wanted to create a version of blackjack where instead visit web page the cards being virtual, a camera would take a picture of a player card.

For clubs it was 0. It served two purposes. The frame rate blackjack on matlab set by an blackjack on matlab clock. The OV is a camera module that caused a great deal amount of trouble for us.

Putty has a key advantage over Blackjack on matlab in that it automatically displays text and data it receives.

The fifth demonstrates cropping. Matlab was vitally important to our project. Our plan to read the data was to read 1 pixel for every 4 rows and for every 4 columns. A challenge of the algorithm was handling aces. Unfortunately, we blackjack on matlab not able to get the camera working.

Camera read is achieved by sending the same start signal, sending what register we're reading from, and then sending the start signal again, but this time with the 'read' register 0x We know we achieved correct signalling because we were able to read register 0x0A which stores the device ID number correctly as 0x Furthermore, we were able to write data to a control register and then correctly read it back.

Code for setting up and using serial with Matlab is very simple and requires specifing the port, baudrate, parity bits, data bits, and flow control. Matlab has to have been told to scan for data on the port. VSYNC is high in between frames and low during data transmission.

We designed them so an ace will count as 11 unless that puts the player score above 21 in which case the ace counts as 1. The basic blackjack on matlab can be seen in the below state diagram. This black corner was removed during extraction by cropping out the large contiguous black section.

So we were going to only same the Y bytes in order to get a greyscale image. The eigth image demonstrates breaking up the image into different sectors to get the color variations. Our original design involved having a camera take a picture of a playing card and using image reconition in Matlab to determine what card was placed.

Next, it resizes the image down to x with equal scaling because the height and width are in the proper ratio.

After that design, we discuss the camera, how it works, and why we think we could not get it working. The camera operation is theoretically very simple. SIOC must be high during this assertion. In one experiment, we displayed every single byte consecutively with the lens cap on just click for source got data along the lines of " 0 0 0 0 0 0 0 1 0 0

Matlab will then do one of three things. Every macropixel shares color data U and V. PCLK going from high to low signals the start of a new pixel. For Matlab, we had to set up a while 1 loop. Our original design consisted of an Atmel ATmegap 8-bit microcontroller, an OV camera module, two PF35T Stepper motors, a timing belt, two gears, and a deck of playing cards. We also specified a timeout. The ninth image demonstrates cropping the suit more. Unlike the rank characters, the suit characters had fairly reliable pixel ratios. Our current design constists of an Atmel ATmegap 8-bit microcontroller and a deck of playing cards. The third image is trimmed. This information is summed up in the two images below. Matlab would send the data to the MCU which would use it as input for a blackjack game. By comparing the ratio of black pixels to all pixels in the cropped frame, the suit could be determined. We were originally planning to do image recognition by determining the ratio of black pixels to white in different areas of the image. It does this by looking for the furthest row or column as applicable with a black pixel. While software was available from the previous labs for the C, we chose OV because we initially had budget constraints and the OV was cheaper. First, it is a video camera so there are many frames a second. Therefore, we took a picture with a cell phone camera and stored the images in a file in the computer. If the player or the dealer gets a second ace, it automatically counts as a 1. The first picture is the original from the camera. One was a vertical line that divides the image in half. A special case was created for the Ace of Spades because the face of the card has an ornate design. There are a vast amount of registers that control a wide array of video configuration options. The MCU, which runs fscanf before every fprintf , receives the signal from Matlab and prints whatever data it needs to print after a short delay. Otherwise, 6 and 9 would be near indistinguishable as would a few other numbers. Aces proved difficult because our casino-quality cards had a black corner above the characters. Matlab then sends the card information to the MCU which runs the blackjack game.