Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/3660
Title: Analysis and development of image edge detection techniques
Researcher: Raman Maini
Guide(s): Aggarwal, Himanshu
Keywords: Digital Image Processing
Computer Engineering
Edge Detection
Noise Reduction Filters
Upload Date: 24-Apr-2012
University: Punjabi University
Completed Date: 23 July, 2011
Abstract: Edge detection is the process that attempts to characterize the intensity changes in terms of the physical processes that have originated them. Edge detection can be used for region segmentation, feature extraction and object boundary description. Edges provide the topology and structure information of objects in an image as different cars can be easily recognized from their body shape. The highway and river from aerial images can be detected in terms of their structure or distribution pattern, which are described by edges. By using edge detection techniques, machine vision and image processing systems can be built for a variety of applications. For example, edge detection can be used in assembly line inspection to detect defects of mechanical parts, for locating the road and recognizing obstacles in automatic vehicle navigation and to detect military targets in remote sensor applications. For medical imaging applications, edge detection and boundary segmentation can be used for locating tumors, blood vessels and rigid bony structures. The separation of a scene into object and its background is an essential step in image interpretation. This is a process that is carried out effortlessly by the human visual system, but when computer vision algorithms are designed to mimic this action, several problems have been encountered. This research work first analysis the goals of edge detection, some basic issues in edge detection and various techniques of edge detection in the literature. During edge detection it is possible to locate intensity changes where edges do not exist due to the presence of noise and quantization of the original image. For similar reasons, it is also possible to completely miss existing edges. The degree of success of an edge-detector depends on its ability to accurately locate true edges.Edge localization is another problem encountered in edge detection. The addition of noise to an image can cause the position of the detected edge to be shifted from its true location.
Pagination: 267p.
URI: http://hdl.handle.net/10603/3660
Appears in Departments:University College of Engineering

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01_title.pdfAttached File34.44 kBAdobe PDFView/Open
02_certificate.pdf55.6 kBAdobe PDFView/Open
03_declaration.pdf65.72 kBAdobe PDFView/Open
04_acknowledgements.pdf108.12 kBAdobe PDFView/Open
05_abstract.pdf99.86 kBAdobe PDFView/Open
06_table of contents.pdf183.79 kBAdobe PDFView/Open
07_list of tables.pdf140.69 kBAdobe PDFView/Open
08_list of figures.pdf254.63 kBAdobe PDFView/Open
09_list of acronyms.pdf25.22 kBAdobe PDFView/Open
10_chapter 1.pdf623.28 kBAdobe PDFView/Open
11_chapter 2.pdf308.06 kBAdobe PDFView/Open
12_chapter 3.pdf3.09 MBAdobe PDFView/Open
13_chapter 4.pdf2 MBAdobe PDFView/Open
14_chapter 5.pdf2.76 MBAdobe PDFView/Open
15_chapter 6.pdf107.18 kBAdobe PDFView/Open
16_bibliography.pdf345.1 kBAdobe PDFView/Open
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