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The paper describes the method of development for the remote sensing data processing to speed up the digitizing workflow. The method is designed to digitize rectangular objects using their approximate spatial positions and provides an automatic estimation of the orientation and aspect ratio. The paper contains a formal statement of the problem of digitizing an object with the desired geometric shape using it’s apriori known spatial position on a source image. The method creates polygonal representations of rectangular spatial objects from one or a few reference points set by an operator. It is based on source image’s pixels clustering using spectral bands as a feature space. The following Hough transform incorporates local direction of intensity gradient to estimate object’s orientation and reduce computational complexity together with low-pass filtering within an accumulation process to improve robustness. It is shown that the developed method can be modified to digitize objects of any analytically described shape. The method is designed to allow easy user interaction without any significant delays and to provide transparent and predictable control of an output object’s polygon size. To investigate the developed method a test dataset with more than 700 rectangular objects was used. The root-mean-square error of object’s points positioning, mean rotation error in polar coordinates and a Jaccard index were used to measure a precision of the digitized objects. The experiment results demonstrate that digitizing workflow is accelerated by 25–40% using the software implementing the developed method without a significant precision loss.

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