Comparison of Image Preprocessing Techniques for Textile Texture Images

Simple item page
dc.categoryJournal Article
dc.contributor.authorRadha, V
dc.date.accessioned2017-03-31T01:22:17Z
dc.date.available2017-03-31T01:22:17Z
dc.date.issued2010
dc.departmentComputer Scienceen_US
dc.description.abstractTexture analysis is an important approach in textile quality control. The investment in automated unit is more economical when reduction in labor cost and associated benefits are considered. Preprocessing in textile image is a crucial initial step before texture analysis is performed. Many preprocessing methods are available in the literature. Datasets are limited by laboratory constraints so that the need is for guidelines on quality and robustness, to proceed experimentation while image are yet restricted. In this paper, the performance of four preprocessing methods are compared namely Contrast adjustment. Intensity adjustment. Histogram equalization, Binarization and Morphological operation. The performances of these methods are evaluated using Peak Signal to Noise Ratio (PSNR) and Mean Square Error (MSE).en_US
dc.identifier.urihttps://ir.avinuty.ac.in/handle/avu/2404
dc.langEnglishen_US
dc.publisher.nameInternational Journal of Engineering Sicences And Technologiesen_US
dc.publisher.typeInternationalen_US
dc.titleComparison of Image Preprocessing Techniques for Textile Texture Imagesen_US
Files
Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
CS_international_2010_012.pdf
Size:
2.57 MB
Format:
Adobe Portable Document Format
Download
Collections
Journal Article