Principal curve detection in complicated graph images

Yuncai Liu; Thomas S. Huang

doi:10.1117/12.441549

20 September 2001 Principal curve detection in complicated graph images

Yuncai Liu, Thomas S. Huang

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.

Citation Download Citation

Yuncai Liu and Thomas S. Huang "Principal curve detection in complicated graph images", Proc. SPIE 4552, Image Matching and Analysis, (20 September 2001); https://doi.org/10.1117/12.441549

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