||Today, digital images is commonly used to preserve and present analogue media. To minimize the need for digital storage space, it is important that the object covers as large part of the image as possible.
This master thesis project presents a robust methodology, based on common edge and line detection techniques, to automatically identify rectangular objects in digital images. The methodology is tailored to identify posters,
photographs and books digitized at the National Library of Sweden (the KB). With the aid of the developed tool, less time and manual labor is required for the KB to crop their digital images.
The methodology has been implemented as a part of DocCrop, a computer program written in Java to automatically
identify and crop documents in digital images.
Three different multi-paged documents supplied by the KB, featuring different characteristics, have been used to evaluate the tool's performance.