The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Aug. 26, 2014
Filed:
Mar. 03, 2010
Kazuto Noguchi, Sakai, JP;
Koichi Kise, Sakai, JP;
Masakazu Iwamura, Sakai, JP;
Yukihito Furuhashi, Hachioji, JP;
Taiji Mine, Chofu, JP;
Kazuto Noguchi, Sakai, JP;
Koichi Kise, Sakai, JP;
Masakazu Iwamura, Sakai, JP;
Yukihito Furuhashi, Hachioji, JP;
Taiji Mine, Chofu, JP;
Osaka Prefecture University Public Corporation, Osaka, JP;
Olympus Corporation, Tokyo, JP;
Abstract
An image retrieval method comprising: a step of extracting at least one query feature vector from a query image on which a subject of the image retrieval is captured, the query feature vector representing a local feature of the query image; a step of accessing an image data base in which a plurality of reference images are stored previously, each reference image being stored in conjunction with learning images generated therefrom and reference feature vectors representing local features of the reference image and the learning images; a comparing step of comparing the query feature vector with the reference feature vectors stored in conjunction with each reference image using an approximate nearest neighbor search to find a reference feature vector approximately nearest to the query feature vector; and a selecting step of selecting a reference image with which the found reference feature vector is stored in conjunction from the reference images as a retrieval result wherein: the learning image is generated by adding a defocus and/or a motion-blur effect likely to occur on capturing the subject to each reference image, the reference feature vectors are extracted from each reference image and the learning image corresponding to the reference image respectively using the scale-space approach, the query feature vector is extracted from the query image using the scale-space approach, and each of the above steps is executed by a computer.