I have a problem in which I want to map the complex plane with black and white square pixels, and then find the largest continuous group of white pixels within a radius of the origin. I know the software which identifies such things is tediously complex, and the best way of doing it is much, much better than the naive while loop I myself would code. Therefore, I have chosen the open source package Image J.
Image J helps “you develop and share reproducible analysis workflows.” I think the problem I want is not so specific that there does not exist a standard module which does exactly what I want. I want to scan an array of black and white pixels, and then sort the groups of white pixels based on size within a certain radius of the origin. Does there exists some purpose built module, more specific than Image J? Image J deals with images, but since my problem is only black and white pixels in 2D, perhaps a module that takes an input file as some non-image .dat file? Perhaps a binary file giving 1/0 for black/white?
I want to ask something like, ``What is the largest square of only white pixels within 100 pixels of the origin ?" (scale up later) Then I will ask, “What is the distribution of the sizes of the squares of decreasing side within a given radius?” My concern is that by formulating the problem in terms of an image file, I have made things much too complicated. Is an image processor like Image J an unneeded layer of complexity? If so, what module lets you tile the plane with square pixels and then examine the distribution for the different tiling functions? I can make an input as an image file, or as binary file where the 1s and 0s are the black an white pixels.
Thank you for your careful consideration that my primary goal is to study the behavior of the tiling functions by which I map the complex plane with black and white pixels, and when I have described the initial condition .dat file for my counting algorithm, I was wondering if image processing software might be the most efficient. On second thought, counting black and white pixels might be something so common that hyper-efficient dedicated modules exist outside of image processing.