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Please use this identifier to cite or link to this item: http://hdl.handle.net/1993/4941

Title: Near Images: A Tolerance Based Approach to Image Similarity and its Robustness to Noise and Lightening
Authors: Shahfar, Shabnam
Supervisor: Peters, James F. (Electrical and Computer Engineering)
Examining Committee: Hossain, Ekram (Electrical and Computer Engineering) Blatz, James (Civil Engineering)
Graduation Date: October 2011
Keywords: Image similarity measures
Tolerance spaces
Near images
Nearness measures
Issue Date: 27-Sep-2011
Abstract: This thesis represents a tolerance near set approach to detect similarity between digital images. Two images are considered as sets of perceptual objects and a tolerance relation defines the nearness between objects. Two perceptual objects resemble each other if the difference between their descriptions is smaller than a tolerable level of error. Existing tolerance near set approaches to image similarity consider both images in a single tolerance space and compare the size of tolerance classes. This approach is shown to be sensitive to noise and distortions. In this thesis, a new tolerance-based method is proposed that considers each image in a separate tolerance space and defines the similarity based on differences between histograms of the size of tolerance classes. The main advantage of the proposed method is its lower sensitivity to distortions such as adding noise, darkening or brightening. This advantage has been shown here through a set of experiments.
URI: http://hdl.handle.net/1993/4941
Appears in Collection(s):FGS - Electronic Theses & Dissertations (Public)

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