Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/6020
Title: A hybrid denoising algorithm for machined image enhancement using evolved operators, Contourlet and 2D – PCA
Researcher: Sivakumar P
Guide(s): Ravi, S
Keywords: 2D-PCA
Wavelet Transforms
Machine Vision
Contourlet Transform
Surface Roughness
Image Denoising.
Upload Date: 31-Dec-2012
University: St. Peter's University
Completed Date: June, 2012
Abstract: Extraction of features of interest from large and possibly heterogeneous image is a crucial task facing many communities of end-users. Researchers have access to highly capable collection platforms operating in a range of spectral bands. With new distribution technologies and data formats making dissemination of this data progressively cheaper and easier, the bottle-neck to successful exploitation of this information rests more than ever on the availability of suitable analysis tools. Image processing is a very computing intensive task, since several low level (pixel level) operations are performed over an image in order to execute a certain task, like edge detection, edge linking, noise removal, dilation, erosion and filtering. In this context, Machine vision has been explored successfully in a variety of tasks such as, sorting and assembling a group of machined parts, checking for microscopic defects in an automotive door panel, etc. Extensive research has been performed on machine vision applications in manufacturing, since it has the advantage of being non-contact and as well faster than the contact methods. Using Machine Vision, it is possible to evaluate and analyze the area of the surface (the information is extracted using an array of sensors) and enable the user to make application specific intelligent decisions. The advantage of the Machine vision based grabbing of the images online is that it does not account for factors like noise and vibrations of machine tool. Machine vision systems need to capture image, extract information using vision sensors and make intelligent decisions. Image denoising involves the manipulation of the image data to produce a visually high quality image. The filtering approach has been proved to be the best when the image is corrupted. The need for quality control and performance testing has become an integral part of the procedure. Surface finish plays an important role in several engineering applications like surface quality of any machined part.
Pagination: 142p.
URI: http://hdl.handle.net/10603/6020
Appears in Departments:Department of Electronics and Communication

Files in This Item:
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01_title.pdfAttached File124.22 kBAdobe PDFView/Open
02_declaration.pdf127.51 kBAdobe PDFView/Open
03_certificate.pdf127.7 kBAdobe PDFView/Open
04_abstract.pdf130.35 kBAdobe PDFView/Open
05_acknowledgements.pdf127.1 kBAdobe PDFView/Open
06_table of contents.pdf146.44 kBAdobe PDFView/Open
07_list of tables.pdf126.88 kBAdobe PDFView/Open
08_list of figures.pdf139.98 kBAdobe PDFView/Open
09_list of symbols.pdf130.56 kBAdobe PDFView/Open
10_chapter 1.pdf4.27 MBAdobe PDFView/Open
11_chapter 2.pdf4.32 MBAdobe PDFView/Open
12_chapter 3.pdf4.2 MBAdobe PDFView/Open
13_chapter 4.pdf4.54 MBAdobe PDFView/Open
14_chapter 5.pdf4.27 MBAdobe PDFView/Open
15_chapter 6.pdf4.25 MBAdobe PDFView/Open
16_chapter 7.pdf4.07 MBAdobe PDFView/Open
17_references.pdf4.25 MBAdobe PDFView/Open


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