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

Orjuela, S. A.; Quiñones, Rolando; Ortiz-Jaramillo, B.; Rooms, Filip; Keyser, Robain De; Philips, Wilfried

doi:10.1117/12.893102

Cited by 2 publications

(1 citation statement)

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“…A) Texture difference measurement. With the aim of leading to an universal automatic system, we have previously proposed a methodology to select optimal image based features for describing AR grades [33]. With this methodology, characteristics from the description between AR grades and the features are quantified and compared using experimental design theory [33].…”

Section: Texture Feature Extractionmentioning

confidence: 99%

Automatic grading of appearance retention of carpets using intensity and range images

Vargas

Ortiz-Jaramillo

Vansteenkiste

et al. 2012

J. Electron. Imaging

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Abstract. Textiles are mainly used for decoration and protection. In both cases, original appearance and its retention are important factors for customers. Therefore, evaluation of appearance parameters are critical for quality assurance purposes, while and after manufacturing, to determine lifetime and/or beauty of textile products. Particularly, appearance retention of textile products is commonly certified with grades, which are currently assigned by human experts. However, manufacturers would prefer a more objective system. In this paper we present an objective system for grading appearance retention, particularly, for textile floor coverings.Changes in appearance are quantified by using linear regression models on texture features extracted from intensity and range images. Range images are obtained by our own laser scanner, reconstructing the carpet surface using two methods that have been previously presented. We extract texture features using a variant of the local binary pattern technique based on detecting those patterns whose frequencies are related to the appearance retention grades. We test models for eight types of carpets. Results show that the proposed approach describes the degree of wear with a precision within the range allowed to human inspectors by international standards. The methodology followed in this experiment has been designed to be general for evaluating global deviation of texture in other types of textiles as well as other surface materials.

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Section: Texture Feature Extractionmentioning

confidence: 99%