Script for batch conversion and algorithms to find rectilinear shapes

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This week, I and Vitalii started off by writing a bash script that takes a set of images from a directory, converts them (one at a time) and saves the converted images in a sub-directory or any other directory. The converted files are saved as TIFF and will have the same file name as the original. Because a single image takes more than 3 minutes to convert using ImageMagick, a batch of image could take quite a while. So, for now we will be using the nohup command to run the conversion in background but will work on parallelizing the conversion which should not be difficult considering that it is embarrassingly parallel.

For the rest of the week, we looked at algorithms which could be useful to detect rectilinear shapes from aerial images. We found that most of the algorithm, for accuracy, take multiple aerial images of the same region, often shot from different angles, to determine any man-made objects on the ground. However, we also found a convincing research article which uses Boldt Algorithm to find rectilinear shapes in aerial imagery.

Up next, analyzing aerial images from Skalanes

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Vitalii, Niraj and I talked about how to proceed with the aerial images from Skalanes. For now we are going to focus on two aspects, identifying possibly anthropomorphic surface features and measuring the extent of the lupine. There are a couple of algorithms that look promising for feature ID but they require stereo images. We will look into doing that next year. There is also at least one approach that uses mono images that they will start with. The automated image conversion scripts they wrote will be used to tune the input characteristics of the images for the algorithm(s). We haven’t decided on an approach yet for the lupine but I did have an idea for doing it based on a color map seeded with human input. It’s on the back of an envelope in the Hopper lab…