Stephanie and I have started examining the beginning steps in building the software for this project. We decided that it would be useful to first noise reduce an image before beginning to transform it. This will hopefully rid the image of randomly placed and unwanted pixels and allow the edges of shapes to become more defined. A noise reduction method that we discovered is median filtering. This involves going through the pixels in an image and, for each one, examining the surrounding pixels, or “neighborhood.” Typically, the neighborhood consists of all the pixels adjacent to the selected pixel. This method then determines the values of these pixels. The value could be the numerical value representing a pixel in grey scale, for instance. We then find the median value of these pixels and use it as the new value for the original pixel.
Once the image has passed noise reduction, we can then begin the process of edge detection. In keeping with an iterative development process, we decided it would be easier to only be concerned with grey scale images first. This way, we can examine each pixel’s grey scale value and turn it either black or white. Then, we can then easily distinguish between black and white and decipher where the edges are. As the images we work with become more complicated, so will our technique. For now, we believe this is a first good step.
In further discussions, we hope to improve our edge detection method, examine how to transform the shapes that we find into 3D, and begin to actually implement some of our ideas.
