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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)
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.