The Library
Indexing images of buildings based on geometrical invariant Hough descriptors
Tools
Li, Chang-Tsun and Yuan, Xiang (2012) Indexing images of buildings based on geometrical invariant Hough descriptors. University of Warwick. Department of Computer Science. (Department of Computer Science Technical report). (Unpublished)
|
PDF
WRAP_Chang-Tsun_cs-rr-450 (1).pdf - Published Version - Requires a PDF viewer. Download (775Kb) | Preview |
Abstract
A CBIR system for retrieving images with specific buildings from databases is proposed in this paper. We exploit the parallelism invariance property of the line features of buildings in images in the derivation of two new geometrically invariant linear feature descriptors. We call these descriptors Hough descriptors as they are extracted from the Hough transform domain. The underlying concept is to utilise the invariance of parallel line features such that the individual edges (local property) can be used in a collective manner to embed their global relationship in the feature descriptors. Upon receiving a query image, the CBIR system transforms the edges detected from the query image into the Hough transform domain. The transform domain is divided into 180 degrees/bins in order to reveal the linear edge distribution. From each bin, the peak percentage profile and distance ratio profile are calculated to serve as the descriptors of images. That is to say that an image descriptor consists of two components (peak percentage profile and distance ratio profile), each with 180 elements. The circular correlations between the peak percentage profile and distance ratio profile of the query image and those of the database images are then taken as the similarity measure for ranking the relevance of the database images to the query.
Item Type: | Report | ||||
---|---|---|---|---|---|
Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||
Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||
Library of Congress Subject Headings (LCSH): | Content-based image retrieval, Hough functions | ||||
Series Name: | Department of Computer Science Technical report | ||||
Publisher: | University of Warwick. Department of Computer Science | ||||
Official Date: | 2012 | ||||
Dates: |
|
||||
Number of Pages: | 24 | ||||
DOI: | CS-RR-450 | ||||
Institution: | University of Warwick | ||||
Theses Department: | Department of Computer Science | ||||
Status: | Not Peer Reviewed | ||||
Publication Status: | Unpublished | ||||
Access rights to Published version: | Open Access (Creative Commons) | ||||
Date of first compliant deposit: | 28 July 2016 | ||||
Date of first compliant Open Access: | 28 July 2016 | ||||
Related URLs: |
Request changes or add full text files to a record
Repository staff actions (login required)
View Item |
Downloads
Downloads per month over past year