JOURNAL ARTICLE

<title>Rotational information in shape description</title>

Ahmed GhaliMohammad F. Daemi

Year: 1996 Journal:   Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE Vol: 2847 Pages: 96-105   Publisher: SPIE

Abstract

Using information theory, this investigation propose a novel technique for shape description which is invariant to translation, rotation and in most cases also to scale. This new numeric shape descriptor is based on the measure of rotational information content of an image. In this paper we first review some popular metric shape description features. These features are then used to analyze the feasibility of using the rotational information for shape description, and by means of a comparative study we show how the rotational information is related to well known metric shape descriptors such as area, circularity and elongation. Finally, the results obtained are discussed and analyzed, and conclusions drawn in terms of the suitability of the technique for shape description in image recognition problems.

Keywords:
Metric (unit) Computer science Rotation (mathematics) Shape analysis (program analysis) Translation (biology) Artificial intelligence Invariant (physics) Computer vision Measure (data warehouse) Scale invariance Active shape model Pattern recognition (psychology) Image (mathematics) Mathematics Data mining Segmentation Engineering

Metrics

1
Cited By
0.48
FWCI (Field Weighted Citation Impact)
1
Refs
0.68
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Topics

Image Retrieval and Classification Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Advanced Image and Video Retrieval Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition
Medical Image Segmentation Techniques
Physical Sciences →  Computer Science →  Computer Vision and Pattern Recognition

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