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An unsupervised method for dominant colour region segmentation in yarn‐dyed fabrics
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Citations
19
References
2013
Year
EngineeringHierarchical Segmentation StructureImage AnalysisPattern RecognitionUnsupervised MethodDyeingEdge DetectionImaging SystemTextile ProcessingMachine VisionTextile TestingMedical Image ComputingOptical Image RecognitionComputer VisionTextile FibreNovel Unsupervised ApproachYarn‐dyed FabricsTexture AnalysisColorizationImage Segmentation
This paper presents a novel unsupervised approach to detect dominant colour regions standing out conspicuously in yarn-dyed fabric images. For a dominant colour region of a yarn-dyed fabric, measured by an imaging system, its individual yarn has an irregular three-dimensional shape resulting in significant colour difference among pixels of the yarn. This difference leads to difficulty in segmenting yarns into dominant colour regions. A probabilistic model is proposed in this study to associate the colour of a dominant colour region with the colours of its yarns. Based on this model, the colour histograms of a dominant colour region are first estimated from those of yarns in a yarn-dyed fabric image. Then, a hierarchical segmentation structure is devised to detect dominant colour regions in the image. Experimental results show that the proposed approach achieves satisfactory performance for dominant colour region segmentation in yarn-dyed fabric images, with high computational efficiency.
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