Object recognition via multi-view inspection using saturation-weighted distributive hue histograms and depth information

Resource type
Thesis type
(Thesis) M.A.Sc.
Date created
2010-07-30
Authors/Contributors
Abstract
A computer vision algorithm is presented for the detection and localization of objects within unknown environments. To search for a specific object within an image, information about the object's appearance is first extracted from database images of the object. To effectively represent the appearance of the object, the Saturation-Weighted Distributive Hue Histogram is presented which encapsulates the intrinsic color information of the object as well as the spatial arrangement of colors within the object's boundaries. These histograms are then searched for in the scene image of the environment. The use of depth information allows searching for objects at depth variant planes in order to achieve scale invariance and to obtain the 3D coordinates of match candidates. A mobile robot platform is employed to move to various locations within the environment and to inspect matching regions by capturing and processing further images.
Document
Identifier
etd6091
Copyright statement
Copyright is held by the author.
Permissions
The author granted permission for the file to be printed and for the text to be copied and pasted.
Scholarly level
Supervisor or Senior Supervisor
Thesis advisor: Saeedi, Parvaneh
Member of collection
Attachment Size
etd6091_JWestell.pdf 9.94 MB