Paper
16 September 1999 Texture and color features for tile classification
Ramon Baldrich, Maria Vanrell, Juan Jose Villanueva
Author Affiliations +
Proceedings Volume 3826, Polarization and Color Techniques in Industrial Inspection; (1999) https://doi.org/10.1117/12.364318
Event: Industrial Lasers and Inspection (EUROPTO Series), 1999, Munich, Germany
Abstract
In this paper we present the results of a preliminary computer vision system to classify the production of a ceramic tile industry. We focus on the classification of a specific type of tiles whose production can be affected by external factors, such as humidity, temperature, origin of clays and pigments. Variations on these uncontrolled factors provoke small differences in the color and the texture of the tiles that force to classify all the production. A constant and non- subjective classification would allow avoiding devolution from customers and unnecessary stock fragmentation. The aim of this work is to simulate the human behavior on this classification task by extracting a set of features from tile images. These features are induced by definitions from experts. To compute them we need to mix color and texture information and to define global and local measures. In this work, we do not seek a general texture-color representation, we only deal with textures formed by non-oriented colored-blobs randomly distributed. New samples are classified using Discriminant Analysis functions derived from known class tile samples. The last part of the paper is devoted to explain the correction of acquired images in order to avoid time and geometry illumination changes.
© (1999) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Ramon Baldrich, Maria Vanrell, and Juan Jose Villanueva "Texture and color features for tile classification", Proc. SPIE 3826, Polarization and Color Techniques in Industrial Inspection, (16 September 1999); https://doi.org/10.1117/12.364318
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Cited by 12 scholarly publications and 1 patent.
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KEYWORDS
Image segmentation

RGB color model

Image classification

Sensors

Cameras

Machine vision

Computer vision technology

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