Content-based image search

US9710491B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-9710491-B2
Application numberUS-61081009-A
CountryUS
Kind codeB2
Filing dateNov 2, 2009
Priority dateNov 2, 2009
Publication dateJul 18, 2017
Grant dateJul 18, 2017

How to read this patent

A practical reading order for non-experts. Skip the full description unless you need deep technical detail.

  1. Title

    What the patent document calls the invention.

  2. Abstract

    A short plain-language summary of the technical disclosure.

  3. Assignees and inventors

    Who owns or filed the patent and who is credited as inventor.

  4. Key dates

    Filing, priority, publication, and grant dates set the timeline.

  5. First independent claim

    The legal scope of protection — read this for what is actually claimed.

  6. CPC / IPC classifications

    Technology tags used to group this patent with similar filings.

  7. Citations and related patents

    Prior art links and similar publications in this corpus.

Abstract

Official abstract text for this publication.

Image descriptor identifiers are used for content-based search. A plurality of descriptors is determined for an image. The descriptors represent the content of the image at respective interest points identified in the image. The descriptors are mapped to respective descriptor identifiers. The image can thus be represented as a set of descriptor identifiers. A search is performed on an index using the descriptor identifiers as search elements. A method for efficiently searching the inverted index is also provided. Candidate images that include at least a predetermined number of descriptor identifiers that match those of the image are identified. The candidate images are ranked and at least a portion thereof are presented as content-based search results.

First claim

Opening claim text (preview).

The invention claimed is: 1. A computer-implemented method for searching a plurality of images, the method comprising: receiving a search query that includes an image; identifying, by a computing device, a plurality of first descriptor identifiers based on the search query, each of the first descriptor identifiers comprising an identifier used to identify a respective descriptor, each descriptor having been calculated over a respective portion of the image comprising a subset of pixels of the image that includes a respective interest point in the image; searching a plurality of indexed images in a search engine inverted index by comparing one or more of the first descriptor identifiers to one or more second descriptor identifiers associated with the indexed images to identify one or more candidate images, wherein the searching comprises; traversing the search engine inverted index to identify a predetermined number of second descriptor identifiers having location identifiers with lowest values; identifying an end-of-document location identifier that follows a largest location identifier value of the predetermined number of second descriptor identifiers having the location identifier with lowest values; identifying a start-of-document location value for a candidate indexed image that is identified by the end-of-document location identifier; and returning the candidate indexed image as a candidate image based on determining the location identifiers of all of the predetermined number of second descriptor identifiers having the lowest location identifier values are greater than or equal to the start-of-document location value; and ranking the one or more candidate images. 2. The computer-implemented method of claim 1 , wherein the search query includes one or more textual words. 3. The computer-implemented method of claim 1 , wherein the search engine inverted index is based on a flat index location space in which the second descriptor identifiers for each of the plurality of indexed images are listed sequentially with an end-of-document identifier following the second descriptor identifiers for each indexed image, and each second descriptor identifier and end-of-document identifier includes a location identifier that indicates their respective location in the flat index location space. 4. The computer-implemented method of claim 1 , wherein the predetermined number of second descriptor identifiers is increased based on a minimum total number of matching second descriptor identifiers for a candidate image in a group of candidate images. 5. The computer-implemented method of claim 1 , wherein the one or more candidate images are ranked based at least in part on one or more selected from the following: a term frequency ranking score, a geometric verification, or a two-dimensional image transformation including one or more of a similarities transformation and an affine transformation. 6. The computer-implemented method of claim 5 , wherein the one or more candidate images are also ranked based on one or more selected from the following: image quality, metadata associated with one or more of the indexed images, and extracted data that is extracted and aggregated from a web page in which the indexed image is published. 7. The computer-implemented method of claim 1 , further comprising: associating at least one of the first descriptor identifiers with a textual word; and performing a text-based search query using the textual word. 8. One or more computer storage memory storing computer-useable instructions that, when used by one or more computing devices, cause the one or more computing devices to perform operations comprising: receiving a search query; identifying a plurality of first descriptor identifiers based on the search query; searching a plurality of indexed images in a search engine inverted index by comparing one or more of the first descriptor identifiers to one or more second descriptor identifiers associated with the indexed images to identify one or more candidate images, each of the one or more second descriptor identifiers comprising an identifier used to identify a respective descriptor, each descriptor having been calculated over a respective portion of a respective indexed image comprising a subset of pixels of the respective indexed image that includes a respective interest point in the respective indexed image, wherein the searching comprises; traversing the search engine inverted index to identify a predetermined number of second descriptor identifiers having location identifiers with lowest values; identifying an end-of-document location identifier that follows a largest location identifier value of the predetermined number of second descriptor identifiers having the location identifier with lowest values; identifying a start-of-document location value for a candidate indexed image that is identified by the end-of-document location identifier; and returning the candidate indexed image as a candidate image based on determining the location identifiers of all of the predetermined number of second descriptor identifiers having the lowest location identifier values are greater than or equal to the start-of-document location value; and ranking the one or more candidate images. 9. The one or more computer storage memory of claim 8 , wherein the search query includes one or more textual words. 10. The one or more computer storage memory of claim 8 , wherein the search query includes one or more images. 11. The one or more computer storage memory of claim 8 , wherein the search engine inverted index is based on a flat index location space in which the second descriptor identifiers for each of the plurality of indexed images are listed sequentially with an end-of-document identifier following the second descriptor identifiers for each indexed image, and each second descriptor identifier and end-of-document identifier includes a location identifier that indicates their respective location in the flat index location space. 12. The one or more computer storage memory of claim 8 , wherein the predetermined number of second descriptor identifiers is increased based on a minimum total number of matching second descriptor identifiers for a candidate image in a group of candidate images. 13. The one or more computer storage memory of claim 8 , wherein the one or more candidate images are ranked based at least in part on one or more selected from the following: a term frequency ranking score, a geometric verification, or a two-dimensional image transformation including one or more of a similarities transformation and an affine transformation. 14. The one or more computer storage memory of claim 13 , wherein the one or more candidate images are also ranked based on one or more selected from the following: image quality, metadata associated with one or more of the indexed images, and extracted data that is extracted and aggregated from a web page in which the indexed image is published. 15. The one or more computer storage memory of claim 8 , the operations further comprising: associating at least one of the first descriptor identifiers with a textual word; and performing a text-based search query using the textual word. 16. A computer device comprising: one or more processors; and one or more computer storage devices storing computer-useable instructions that, when used by the one or more processors, cause the one or more processors to: identify a plurality of first descriptor identifiers based on a search query; search a plurality of indexed images in a search engine inverted index b

Assignees

Inventors

Classifications

  • Indexing; Web crawling techniques · CPC title

  • using colour · CPC title

  • Indexing structures · CPC title

  • Natural language query formulation · CPC title

  • Information retrieval; Database structures therefor; File system structures therefor · CPC title

Patent family

Related publications grouped by family.

External sources

Frequently asked questions

Answers are generated from the same data shown on this page.

What does patent US9710491B2 cover?
Image descriptor identifiers are used for content-based search. A plurality of descriptors is determined for an image. The descriptors represent the content of the image at respective interest points identified in the image. The descriptors are mapped to respective descriptor identifiers. The image can thus be represented as a set of descriptor identifiers. A search is performed on an index usi…
Who is the assignee on this patent?
Ke Qifa, Liu Ming, Li Yi, and 1 more
What technology area does this patent fall under?
Primary CPC classification G06F16/5838. Mapped technology areas include Physics.
When was this patent published?
Publication date Tue Jul 18 2017 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 8 related publications on this page (citations in our corpus or others sharing the same primary CPC).