Framework for image search in visual databases using keypoints, their descriptors and geometric constraints

• Main Author: Ang, Zixuan
• Other Authors: Andrzej Stefan Sluzek
• Format: Final Year Project
• Language: English
• Published: 2011
• Subjects: 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
• Online Access: http://hdl.handle.net/10356/44206
• Institution: Nanyang Technological University

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.