Classification of painting cracks for content-based analysis

Bibliographic reference:

F.S. Abas and K. Martinez, Classification of painting cracks for content-based analysis.

Available at: http://eprints.ecs.soton.ac.uk/7294/1/spie_cracks.pdf

Extract:

2. APPLICATION SCENARIO

The capabilities of image analysis and processing can aid conservators if the process can provide them with the functionalities that manual processes fail to do. Among the common problems of manual defect screening are time consumption and the risk of further damage. Required information should be retrieved correctly (i.e as close as possible to the users’ individual perception) and consumes considerably less time and effort. The following sections briefly outline potential application scenarios from a user point of view.

Dublin Core Metadata:

Title : Classification of painting cracks for content-based analysis
Creator : F.S. Abas and K. Martinez

Subject : cracks/ classification/ content analysis/ clustering
Description : "In this paper we present steps taken to implement a content-based analysis of crack patterns in paintings. Cracks are first detected using a morphological top-hat operator and grid-based automatic thresholding. From a 1-pixel wide representation of crack patterns, we generate a statistical structure of global and local features from a chain-code based representation. A well structured model of the crack patterns allows post-processing to be performed such as pruning and high-level feature extraction. High-level features are extracted from the structured model utilising information mainly based on orientation and length of line segments. Our strategy for classifying the crack patterns makes use of an unsupervised approach which incorporates fuzzy clustering of the patterns. We present results using the fuzzy k-means technique."

Publisher : Intelligence, Agents, Multimedia Group, Department of Electronics and Computer Science, University of Southampton, United Kingdom, S017 1BJ.
Date : None
Type : Text
Format : pdf

Identifier : http://eprints.ecs.soton.ac.uk/7294/1/spie_cracks.pdf
Source: None
Language : En
Relation : -
Coverage : United Kingdom
Rights : Intelligence, Agents, Multimedia Group, Department of Electronics and Computer Science, University of Southampton, United Kingdom, S017 1BJ.