Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/20616
Title: Texture defect identification rectification pattern design coloring and animation using analysis and synthesis
Researcher: Karth1keyani, V
Guide(s): Duraiswamy, K
Keywords: SYNTHESIS
TEXTURE DEFECT IDENTIFICATION
Upload Date: 8-Jul-2014
University: Periyar University
Completed Date: 01/06/2007
Abstract: newline This Thesis is mainly concerned with Identification of Defect using Texture newlineAnalysis Rectification of Defect using Texture Synthesis generating a new Pattern newlineDesign Coloring the Gray scale image by extracting the color from some other image and newlineTexture Animation using Synthesis newlineThe benefits of time and cost of defect identification and rectification is associated newlinewith this Many different techniques and methods are used to identify the defects But newlineTexture Analysis and Synthesis are the best techniques This is more useful to Textile newlineIndustry newlineEver since from the year 1965 to till date many researchers have invested their newlineefforts in the area of Texture analysis In this thesis analysis is made to identify the newlinedefects Nine properties are used for analysis They are coarseness contrast complexity newlinestrength busyness energy entropy correlation and homogeneity Till date from the newlineliterature survey it is found that no attempt has been made to identify the defect by texture newlineanalysis The aim of this thesis is to identify and rectify the defect in few seconds newlineSynthesis is made to rectify the defect The multiple pixel based texture synthesis newlinealgorithm has been used From this algorithm the defects are rectified Any type of defect newlinecan be rectified The output size may be of any size Synthesis can be done by giving the newlinevalues of output size block size and the overlap size From this a different synthesized newlineresult can be generated newlineThis is an innovative work From the analysis and the synthesis a new pattern has newlinebeen generated The output of an analysis is given to an input to the synthesis In analysis newlinefind the minimum maximum and the average values of each property This is a new input newlineto the synthesis The synthesis algorithm will produce more results These results are a newlinenew pattern design newlineConversion of gray scale image to a coland image is presented Color is not newlineextracted from the color palette It will be collected from one of the input image Two newlineinput image are given One is gray scale image and another one is a color image
Pagination: xix, 153p.
URI: http://hdl.handle.net/10603/20616
Appears in Departments:Department of Computer Science

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01_title.pdfAttached File13.71 kBAdobe PDFView/Open
02_declaration.pdf15.43 kBAdobe PDFView/Open
03_certificate.pdf12.25 kBAdobe PDFView/Open
04_acknowledgement.pdf28.01 kBAdobe PDFView/Open
05_contents.pdf22.74 kBAdobe PDFView/Open
06_list of tables,figures,acronyms.pdf45.03 kBAdobe PDFView/Open
07_abstract.pdf19.71 kBAdobe PDFView/Open
08_chapter 1.pdf144.15 kBAdobe PDFView/Open
09_chapter 2.pdf717.24 kBAdobe PDFView/Open
10_chapter 3.pdf408.66 kBAdobe PDFView/Open
11_chapter 4.pdf904.86 kBAdobe PDFView/Open
12_chapter 5.pdf239.22 kBAdobe PDFView/Open
13_chapter 6.pdf188.67 kBAdobe PDFView/Open
14_chapter 7.pdf43.45 kBAdobe PDFView/Open
15_references.pdf163.53 kBAdobe PDFView/Open


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