20 September 2001 Principal curve detection in complicated graph images
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Proceedings Volume 4552, Image Matching and Analysis; (2001) https://doi.org/10.1117/12.441549
Event: Multispectral Image Processing and Pattern Recognition, 2001, Wuhan, China
Abstract
Finding principal curves in an image is an important low level processing in computer vision and pattern recognition. Principal curves are those curves in an image that represent boundaries or contours of objects of interest. In general, a principal curve should be smooth with certain length constraint and allow either smooth or sharp turning. In this paper, we present a method that can efficiently detect principal curves in complicated map images. For a given feature image, obtained from edge detection of an intensity image or thinning operation of a pictorial map image, the feature image is first converted to a graph representation. In graph image domain, the operation of principal curve detection is performed to identify useful image features. The shortest path and directional deviation schemes are used in our algorithm os principal verve detection, which is proven to be very efficient working with real graph images.
© (2001) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Yuncai Liu, Yuncai Liu, Thomas S. Huang, Thomas S. Huang, } "Principal curve detection in complicated graph images", Proc. SPIE 4552, Image Matching and Analysis, (20 September 2001); doi: 10.1117/12.441549; https://doi.org/10.1117/12.441549
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