Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/44206
Title: Framework for image search in visual databases using keypoints, their descriptors and geometric constraints
Authors: Ang, Zixuan
Keywords: DRNTU::Engineering::Computer science and engineering::Computing methodologies::Image processing and computer vision
DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval
Issue Date: 2011
Abstract: Image matching and retrieval is one of the most important areas of computer vision. The key objective of image matching is detection of near-duplicate images. This chapter discusses an extension of this concept, namely, the retrieval of near-duplicate image fragments. We assume no a’priori information about visual contents of those fragments. The number of such fragments in an image is also unknown. Therefore, we address the problem and propose the solution based purely on visual characteristics of image fragments. The method combines two techniques: a local image analysis and a global geometry synthesis. In the former stage, we analyze low-level image characteristics, such as local intensity gradients or local shape approximations. In the latter stage, we formulate global geometrical hypotheses about the image contents and verify them using a probabilistic framework.
URI: http://hdl.handle.net/10356/44206
Rights: Nanyang Technological University
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
SCE10-0240.pdf
  Restricted Access
Framework for image search in visual databases using keypoints, their descriptors and geometric constraints1.27 MBAdobe PDFView/Open

Page view(s) 50

249
checked on Oct 21, 2020

Download(s) 50

14
checked on Oct 21, 2020

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.