Please use this identifier to cite or link to this item: http://hdl.handle.net/10603/253350
Title: Studies on visual saliency detection models and their applications in image segmentation and image compression
Researcher: Diana andrushia A
Guide(s): Thangarajan R
Keywords: Engineering and Technology,Computer Science,Computer Science Information Systems
Image segmentation
visual saliency
University: Anna University
Completed Date: 2018
Abstract: Humans can be aware of or understand the environment they live in newlinefrom different levels of observation and participation. This is mainly due to newlinethe innate ability of the human brain in processing visual information by newlinevirtue of abundance of data observed and accumulated over years of newlineexistence. Saliency detection in a visual field is another unparalleled ability of newlinethe human brain. The brain without any conscious effort immediately draws newlineits attention to any salient of prominent features present in an image or scene. newlineWhen the ability of automatically identifying the important regions of an newlineimage or scene, it would serve as an indispensable tool for many applications newlinein the domain of computer vision, image analysis and artificial intelligence. newlineThis research work mainly focuses on visual information processing of images or scenes with regard to saliency detection. Visual scenes may represent various aspects of human day to day affairs such as newlinemundane tasks, arts, holiday outs. Important or salient content of an image newlinegenerally stands out from the rest of the image. Obviously, analysis of images newlinedemands high computational power, abundance of data, and efficient learning newlinealgorithms. Feature engineering is also required to aid machine learning newlinealgorithms to identify which part of an image contains important information newlinewith respect to the rest other parts. This means lesser amount of data, simpler newlinemodels, and more accuracy with lower variance.. newline newline
Pagination: xx, 145p.
URI: http://hdl.handle.net/10603/253350
Appears in Departments:Faculty of Information and Communication Engineering

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02_certificates.pdf1.02 MBAdobe PDFView/Open
03_abstract.pdf13.13 kBAdobe PDFView/Open
04_acknowledgment.pdf4.6 kBAdobe PDFView/Open
05_contents.pdf33.06 kBAdobe PDFView/Open
06_chapter1.pdf374.99 kBAdobe PDFView/Open
07_chapter2.pdf243.41 kBAdobe PDFView/Open
08_chapter3.pdf846.66 kBAdobe PDFView/Open
09_chapter4.pdf1.58 MBAdobe PDFView/Open
10_chapter5.pdf708.58 kBAdobe PDFView/Open
11_chapter6.pdf588.96 kBAdobe PDFView/Open
12_conclusion.pdf29.03 kBAdobe PDFView/Open
13_references.pdf170.79 kBAdobe PDFView/Open
14_publications.pdf127.81 kBAdobe PDFView/Open
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