Abstract
Two new simple but fast and pretty efficient approaches for contour data detection, extraction and approximation are presented in this paper. The High-Pass Filter (HPF) method, designed to detect and extract contours from greyscale images is the first presented method. It operates in spectral domains either of the Periodic Haar Piecewise-Linear (PHL) transform or the Haar Wavelet one. The other presented method, known as the Segments Distances Ratios (SDR) approach, is used, in turn, to approximate the contour lines given by the HPF method. Its spatial approximation accuracy is carefully investigated and reported as well as referred to the universally recognized Ramer algorithm. Efficiency of both presented methods as well as their performance aspects are finally discussed and concluded.
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Acknowledgements
This work was partially supported by The Horizon 2020 project SCISSOR - Security In trusted SCADA and smart-grids (Grant agreement no: 644425) and also by The Polish National Centre for Research and Development (NCBR), as a part of the Project no. DZP/RID-I-68/14/NCBIR/2016 (RID - InPreDo).
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Baran, R., Dziech, A., Wassermann, J. (2017). Contour Extraction and Compression Scheme Utilizing Both the Transform and Spatial Image Domains. In: Dziech, A., Czyżewski, A. (eds) Multimedia Communications, Services and Security. MCSS 2017. Communications in Computer and Information Science, vol 785. Springer, Cham. https://doi.org/10.1007/978-3-319-69911-0_1
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