Shape-Based co-occurrence matrices for defect classification

Authors:
Rami Rautkorpi;Jukka Iivarinen
Affiliations:
Laboratory of Computer and Information Science, Helsinki University of Technology, Finland;Laboratory of Computer and Information Science, Helsinki University of Technology, Finland
Venue:
SCIA'05 Proceedings of the 14th Scandinavian conference on Image Analysis
Year:
2005

Citing 5
Cited 1

Review of shape coding techniques

Image and Vision Computing
Computer Processing of Line-Drawing Images

ACM Computing Surveys (CSUR)
An Adaptive Texture and Shape Based Defect Classification

ICPR '98 Proceedings of the 14th International Conference on Pattern Recognition-Volume 1 - Volume 1
Introduction to MPEG-7: Multimedia Content Description Interface

Introduction to MPEG-7: Multimedia Content Description Interface
Defect image classification and retrieval with MPEG-7 descriptors

SCIA'03 Proceedings of the 13th Scandinavian conference on Image analysis

Enhanced anomaly detection in wire ropes by combining structure and appearance

Pattern Recognition Letters

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper discusses two statistical shape descriptors, the Edge Co-occurrence Matrix (ECM) and the Contour Co-occurrence Matrix (CCM), and their use in surface defect classification. Experiments are run on two image databases, one containing metal surface defects and the other paper surface defects. The extraction of Haralick features from the matrices is considered. The descriptors are compared to other shape descriptors from e.g. the MPEG-7 standard. The results show that the ECM and the CCM give superior classification accuracies.