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Real-time texture error detection on textured surfaces with compressed sensing

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Abstract

We present a real-time approach to detect and localise defects in grey-scale textures within a Compressed Sensing framework. Inspired by recent results in texture classification, we use compressed local grey-scale patches for texture description. In a first step, a Gaussian Mixture model is trained with the features extracted from a handful of defect-free texture samples. In a second step, the novelty detection of texture samples is performed by comparing each pixel to the likelihood obtained in the training process. The inspection stage is embedded into a multi-scale framework to enable real-time defect detection and localisation. The performance of compressed grey-scale patches for texture error detection is evaluated on two independent datasets. The proposed method is able to outperform the performance of non-compressed grey-scale patches in terms of accuracy and speed.

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Authors and Affiliations

  1. MVTec Software GmbH, Neherstr. 1, 81675, München, Germany

    T. Böttger & M. Ulrich

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  1. T. Böttger
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  2. M. Ulrich
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Correspondence to T. Böttger.

Additional information

This paper uses the materials of the report submitted at the 9th Open German-Russian Workshop on Pattern Recognition and Image Understanding, held in Koblenz, December 1–5, 2014 (OGRW-9-2014).

The article is published in the original.

Tobias Böttger studied Mathematics in Science and Engineering at the Technische Universität München (TUM) and received his MSc degree in 2013. He is currently working toward the PhD degree at the Research department of MVTec Software GmbH. His research interests spread between the areas of machine learning and computer vision, with special focus on visual object tracking and optical character recognition.

Markus Ulrich studied Geodesy and Remote Sensing at the Technische Universität München (TUM) and received his PhD from TUM in 2003. In the same year, he joined the Research and Development department at MVTec Software GmbH as a software engineer and became manager for Research and Development in 2008 heading the Research Team. Since 2005, Markus Ulrich is also a guest lecturer at TUM, where he teaches close-range photogrammetry. Since 2013, he is a guest lecturer at Karlsruhe Institute of Technology (KIT) as well, where he teaches machine vision.

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Böttger, T., Ulrich, M. Real-time texture error detection on textured surfaces with compressed sensing. Pattern Recognit. Image Anal. 26, 88–94 (2016). https://doi.org/10.1134/S1054661816010053

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