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Image Pyramid for Automatic Segmentation of Fabric Defects

Publication Type : Conference Paper

Publisher : Computational Vision and Bio Inspired Computing, Springer International Publishing, Cham .

Source : Computational Vision and Bio Inspired Computing, Springer International Publishing, Cham (2018)

Url : https://link.springer.com/chapter/10.1007%2F978-3-319-71767-8_49

ISBN : 9783319717678

Campus : Coimbatore

School : School of Engineering

Department : Computer Science

Year : 2018

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.

Cite this Research Publication : A. Sarkar and Padmavathi, S., “Image Pyramid for Automatic Segmentation of Fabric Defects”, in Computational Vision and Bio Inspired Computing, Cham, 2018.

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