Automatic Characterization of the Visual Appearance of Industrial Materials through Colour and Texture Analysis: An Overview of Methods and Applications
Author(s) -
Elena González,
Francesco Bianconi,
Marcos X. Álvarez,
Stefano Saetta
Publication year - 2013
Publication title -
advances in optical technologies
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.124
H-Index - 25
eISSN - 1687-6407
pISSN - 1687-6393
DOI - 10.1155/2013/503541
Subject(s) - computer science , grading (engineering) , context (archaeology) , characterization (materials science) , texture (cosmology) , artificial intelligence , taxonomy (biology) , class (philosophy) , quality (philosophy) , engineering drawing , image (mathematics) , engineering , materials science , nanotechnology , paleontology , philosophy , civil engineering , biology , botany , epistemology
We present an overview of methods and applications of automatic characterization of the appearance of materials through colour and texture analysis. We propose a taxonomy based on three classes of methods (spectral, spatial, and hybrid) and discuss their general advantages and disadvantages. For each class we present a set of methods that are computationally cheap and easy to implement and that was proved to be reliable in many applications. We put these methods in the context of typical industrial environments and provide examples of their application in the following tasks: surface grading, surface inspection, and content-based image retrieval. We emphasize the potential benefits that would come from a wide implementation of these methods, such as better product quality, new services, and higher customer satisfaction
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