Dilated contour extraction and component labeling algorithm for object vector representation

Alexei N. Skourikhine

doi:10.1117/12.613839

30 August 2005 Dilated contour extraction and component labeling algorithm for object vector representation

Alexei N. Skourikhine

Proceedings Volume 5916, Mathematical Methods in Pattern and Image Analysis; 59160W (2005) https://doi.org/10.1117/12.613839
Event: Optics and Photonics 2005, 2005, San Diego, California, United States

Abstract

Object boundary extraction from binary images is important for many applications, e.g., image vectorization, automatic interpretation of images containing segmentation results, printed and handwritten documents and drawings, maps, and AutoCAD drawings. Efficient and reliable contour extraction is also important for pattern recognition due to its impact on shape-based object characterization and recognition. The presented contour tracing and component labeling algorithm produces dilated (sub-pixel) contours associated with corresponding regions. The algorithm has the following features: (1) it always produces non-intersecting, non-degenerate contours, including the case of one-pixel wide objects; (2) it associates the outer and inner (i.e., around hole) contours with the corresponding regions during the process of contour tracing in a single pass over the image; (3) it maintains desired connectivity of object regions as specified by 8-neighbor or 4-neighbor connectivity of adjacent pixels; (4) it avoids degenerate regions in both background and foreground; (5) it allows an easy augmentation that will provide information about the containment relations among regions; (6) it has a time complexity that is dominantly linear in the number of contour points. This early component labeling (contour-region association) enables subsequent efficient object-based processing of the image information.

Citation Download Citation

Alexei N. Skourikhine "Dilated contour extraction and component labeling algorithm for object vector representation", Proc. SPIE 5916, Mathematical Methods in Pattern and Image Analysis, 59160W (30 August 2005); https://doi.org/10.1117/12.613839

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