Optimizing feature extraction in image analysis using experimented designs: a case study evaluating texture algorithms for describing appearance retention in carpets

S. A. Orjuela; R. A. Quinones; B. Ortiz-Jaramillo; F. Rooms; R. De Keyser; W. Philips

doi:10.1117/12.893102

9 September 2011 Optimizing feature extraction in image analysis using experimented designs: a case study evaluating texture algorithms for describing appearance retention in carpets

S. A. Orjuela, R. A. Quinones, B. Ortiz-Jaramillo, F. Rooms, R. De Keyser, W. Philips

Author Affiliations +

Proceedings Volume 8136, Mathematics of Data/Image Pattern Coding, Compression, and Encryption with Applications XIII; 81360F (2011) https://doi.org/10.1117/12.893102
Event: SPIE Optical Engineering + Applications, 2011, San Diego, California, United States

Abstract

When performing image analysis, one of the most critical steps is the selection of appropriate techniques. A huge amount of features can be extracted from several techniques and the selection is commonly performed based on expert knowledge. In this paper we present the theory of experimental designs as a tool for an objective selection of techniques in image analysis domain. We present a study case for evaluating appearance retention in textile floor coverings using texture features. The use of experimental design theory permitted to select an optimal set of techniques for describing the texture changes due to degradation.

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S. A. Orjuela, R. A. Quinones, B. Ortiz-Jaramillo, F. Rooms, R. De Keyser, and W. Philips "Optimizing feature extraction in image analysis using experimented designs: a case study evaluating texture algorithms for describing appearance retention in carpets", Proc. SPIE 8136, Mathematics of Data/Image Pattern Coding, Compression, and Encryption with Applications XIII, 81360F (9 September 2011); https://doi.org/10.1117/12.893102

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