Follow the Line
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This is due to how the intensity values are stretched. Since the new image has exactly the same number of pixels as the old image the new image still has many pixels intensity values that do not exist and therefore show up as gaps in the histogram. Adding another filter like a mean blur would cause the histogram to become more solid again as the gaps would be filled due to smoothing of the image. Next we need to start focusing on extracting the actual lines in the images.
Edge Detection In order to follow the line we need to extract properties from the image that we can use to steer the robot in the right direction. The next step is to identify or highlight the line with respect to the rest of the image. We can do this by detecting the transition from background tile to the line and then from the line to the background tile. This detection routine is known as edge detection. The way we perform edge detection is to run the image through a convolution filter that is 'focused' on detecting line edges.
A convolution filter is a matrix of numbers that specify values that are to be multiplied, added and then divided from the image pixels to create the resulting pixel value. To learn more about convolution filters have a look at our help section. We will start with the following convolution matrix that is geared to detect edges: Edge Detection Here are two sample images with the convolution edge detection matrix run after normalization: Also note that the detected lines are quite faint and sometimes even broken.
This is largely due to the small 3x3 neighborhood that the convolution filter looks at.
I love this game it is awesome. Next we need to start focusing on extracting the actual lines in the images. Advanced Region Filter Italy. USD - Change Currency. If you want more titles like this, then check out Line or Mmm Fingers.
It is easy to see a very large difference between the line and the tile from a global point of view as how you and I look at the images but from the image pixel point of view it is not as easy. To get a better result we need to perform some modifications to our current operations.
Follow a Line, Can you lead this dot along the winding path? It's a challenge that's tougher than it looks. Elegant and simple finger-runner. Just keep your finger on the screen, stay inside the line and walk through randomly generated maze. Don't step into obstacles.
Modified Line Detection To better highlight the line we are going to: Use a larger filter; instead of a 3x3 neighborhood we will use a 5x5. This will result in larger values for edges that are "thicker". We will use the following matrix: Further reduce the speckling issue we will square the resulting pixel value.
This causes larger values to become larger but smaller values to remain small. The result is then normalized to fit into the pixel value range.
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Threshold the final image by removing any pixels lower than a 40 intensity value. The results of this modified technique: We can now continue to the next step which is how to understand these images in order to map the results to left and right motor pulses. Center of Gravity There are many ways we could translate the resulting image intensities into right and left motor movements. A simple way would be to add up all the pixel values of the left side of the image and compare the result to the right side.
Based on which is more the robot would move towards that side. At this point, however, we will use the COG or Center of Gravity of the image to help guide our robot. The COG of an object is the location where one could balance the object using just one finger. In image terms it is where one would balance all the white pixels at a single spot. The COG is quick and easy to calculate and will change based on the object's shape or position in an image.
To calculate the COG of an image add all the x,y locations of non-black pixels and divide by the number of pixels counted. The resulting two numbers one for x and the other for y is the COG location. When the COG is to the right of the center of screen, turn on the left motor for a bit. When the COG is on the left, turn on the right motor.
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This app is only available on the App Store for iOS devices. Sep 12, Version 1.
Follow the Line
Information Seller Crimson Pine Games sp. Compatibility Requires iOS 9.
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- Follow the Line.
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Compatible with iPhone, iPad, and iPod touch. Game Center Challenge friends and check leaderboards and achievements.
