Abstract
Automatic fabric detection is required by the textile industries to improve their quality. For extraction of defective fabric areas, process of segmentation is needed to distinguish the defective region from the background. This paper investigates a method to construct image pyramid by Gaussian method wherein the images are decomposed into multiple levels. Noises are removed and features are extracted for fifteen different defects. Various levels were analyzed and the best level required for proper segmentation is identified for each defect. Region based watershed segmentation and edge based Sobel edge segmentation were experimented on multiple levels. The base level and best level of all decomposed images were compared for all fabric defects investigated.
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Sarkar, A., Padmavathi, S. (2018). Image Pyramid for Automatic Segmentation of Fabric Defects. In: Hemanth, D., Smys, S. (eds) Computational Vision and Bio Inspired Computing . Lecture Notes in Computational Vision and Biomechanics, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-319-71767-8_49
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DOI: https://doi.org/10.1007/978-3-319-71767-8_49
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