A Theory of Multiscale, Curvature-Based Shape Representation for Planar Curves
IEEE Transactions on Pattern Analysis and Machine Intelligence
Unsupervised Segmentation of Color-Texture Regions in Images and Video
IEEE Transactions on Pattern Analysis and Machine Intelligence
Curves and surfaces for CAGD: a practical guide
Curves and surfaces for CAGD: a practical guide
SIMPLIcity: Semantics-Sensitive Integrated Matching for Picture LIbraries
IEEE Transactions on Pattern Analysis and Machine Intelligence
A Hierarchical System for Efficient Image Retrieval
ICPR '96 Proceedings of the International Conference on Pattern Recognition (ICPR '96) Volume III-Volume 7276 - Volume 7276
Invariant matching and identification of curves using B-splines curve representation
IEEE Transactions on Image Processing
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We present an approach for representing digital image by using B-spline curve fittings to the segmented digital image. The image is first segmented to form isolated contours and regions. Each region's boundary (contour) is thereafter approximated by a B-spline curve. A cubic B-spline curve is used instead of a far higher degree Bezier curve to approximate the boundary because it has a local control property and is less wiggly. The obtained B-spline curves are collectively composed and used to represent the original image. One of the many practical applications lies in image retrieval, clustering and classification where general shapes, arrangement and composition of control points of those obtained B-spline curves are used to compare and find similarity between images in a collection.