Content-based retrieval from image databases using sketched queries

Content Provider	Semantic Scholar
Author	Chalechale, Abdolah
Copyright Year	2005
Abstract	Searching multimedia databases using features extracted from the content is currently an active research area. This thesis presents novel feature extraction approaches for content-based image retrieval when the query image is a hand-drawn black and white sketch. To facilitate robust man-machine interfaces, we accept query images with no color and texture attributes. Special attention is given to the scale and rotation invariance properties since the query and database images may vary in size and rotation angle. Several applicable techniques within the literature are studied for these conditions. The goal is to present the user with a subset of images that are more similar to the sketched query. New affine transform invariant feature extraction techniques are proposed to improve retrieval performance, and reduce the extraction and search times. The techniques are tested both generally for multi-component images and particularly for isolated shapes. The solutions are discussed for each specific application. Finally, signature-based document retrieval, which explores document retrieval from databases using human signatures, is investigated on an individual basis. Two different approaches based on spatial distribution of edge pixels are proposed for general sketch-based image retrieval. Here, the database images consist of multiple complex objects within an inhomogeneous background. One of the methods is an improved version of another, which increases retrieval performance. Both techniques exhibit scale invariance property resulting from size normalization. Rotation invariance property is achieved by employing the magnitude of the Fourier transform coefficients in two different ways. A database including 4000 artwork and photograph images is used for the experiments.
File Format	PDF HTM / HTML
Alternate Webpage(s)	https://ro.uow.edu.au/cgi/viewcontent.cgi?article=1249&context=theses&httpsredir=1&referer=
Alternate Webpage(s)	http://www.library.uow.edu.au/adt-NWU/uploads/approved/adt-NWU20050623.121943/public/02Whole.pdf
Language	English
Access Restriction	Open
Content Type	Text
Resource Type	Article