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Proceedings Paper

Recognition of line patterns using moments
Author(s): Mohammad Farhang Daemi; Harish K. Sardana; Mohammad K. Ibrahim
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Paper Abstract

Most reliable features that can be readily extracted from intensity images comprising of line segments: both straight and curved. Most applications rely on the recognition of such line patterns. Fourier Descriptors, which are widely used, require the patterns to be closed and binary. Other techniques which are based on the chain codes or vectorization have quantization errors and therefore need additional preprocessing. Furthermore, almost all the description methods for line patterns inherently have an element of 'tracing' involved in them and their generalization to grey scale or multi-colored patterns is limited. A novel global shape description technique based on edge segments is used for recognition of line patterns. This approach extends the boundary based representation to generalized edge patterns that may have segments which are straight, curved, crossing or open. A novel representation of Edge Moments (EM) is used for shape description with a novel normalization. The invariant features may be formed by using standard (invariant) moments. This has led to development of Edge standard moments (ESM). The power of the method is demonstrated for recognition of 3-D polyhedral objects.

Paper Details

Date Published: 20 October 1993
PDF: 12 pages
Proc. SPIE 2028, Applications of Digital Image Processing XVI, (20 October 1993); doi: 10.1117/12.158641
Show Author Affiliations
Mohammad Farhang Daemi, Univ. of Nottingham (United Kingdom)
Harish K. Sardana, Univ. of Nottingham (United Kingdom)
Mohammad K. Ibrahim, Univ. of Nottingham (United Kingdom)


Published in SPIE Proceedings Vol. 2028:
Applications of Digital Image Processing XVI
Andrew G. Tescher, Editor(s)

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