METHOD, APPARATUS, AND NON-TRANSITORY COMPUTER-READABLE STORAGE MEDIUM FOR MATCHING TEXT TO IMAGES

• US 20160335493A1
• Filed: 05/13/2016
• Published: 11/17/2016
• Est. Priority Date: 05/15/2015
• Status: Abandoned Application

• Current Assignee: Ricoh Company Limited
• Original Assignee: Jichuan Zheng, Qian Li, Shanshan Jiang
• Inventors: JIANG, Shanshan, LI, Qian, ZHENG, Jichuan
• Application Number:
  US15/154,490
• Publication Number:
  US 20160335493A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06V 2201/10 Recognition assisted with metadata
• CPC Class Codes: G06V 30/413 Classification of content, e.g. text, photographs or tables
• CPC Class Codes: G06V 30/414 Extracting the geometrical structure, e.g. layout tree; Block segmentation, e.g. bounding boxes for graphics or text

Abstract

A method and apparatus are provided for acquiring a plurality of images and corresponding text comments that includes a plurality of segments; retrieving, based on a pre-established key-word library, a key word of each segment; and matching a segment, based on the key word retrieved from the segment, to a corresponding image selected from the plurality of images.

Claims

1. A method for matching text to images, comprising:

acquiring a plurality of images and corresponding text comments that includes a plurality of segments;

retrieving, based on a pre-established key-word library, a key word of each segment; and

matching a segment, based on the key word retrieved from the segment, to a corresponding image selected from the plurality of images.

2. The method according to claim 1, wherein the method further comprises:

selecting a key word matched to an image, from the key-word library or all of the key words retrieved from the text comment, and labeling the image with the key word as a tag, so as to label each image,

and the matching includes;

assigning a segment as a candidate segment; and

determining, based on the tag of each image and the key word of the candidate segment, an image that corresponds to the candidate segment from the plurality of images.

3. The method according to claim 2, wherein the labeling includes:

identifying an image, based on the key-word library or the key word retrieved from the text comments, so as to get an image character,

selecting a key word when the image character identified from the image is matched with the key word, and

labeling the image with the key word as a tag.

4. The method according to claim 3, wherein the determining includes:

calculating, based on the tag of an image and the key word of the candidate segment, a correlative-value of the image with the candidate segment; and

designating an image corresponded to the candidate segment if the correlative-value is higher than an predetermined value.

5. The method according to claim 4, wherein the key-word library includes:

a first candidate word retrieved from another text comment that is different from the text comment about the plurality of images; and

a second candidate word retrieved from the tag of other image different with the plurality of images.

6. The method according to claim 5, wherein the first candidate word and the second candidate word contain a word belong to a classification selected from a group including a subject, scene, image metadata, positional relationship between the plurality of images, and a high-frequency word.

7. The method according to claim 6, wherein each classification has a predetermined weighting factor, and a weighted number of the tags correlated to the candidate segment is calculated as the correlative-value of the image to the candidate segment.

8. The method according to one of claim 1, wherein the acquiring includes:

obtaining the text comment and segmenting the text comment into the plurality of segments by comma, semi-colon, full-stop, or paragraph.

9. An apparatus for matching text to images, comprising:

processing circuitry configured to

acquire a plurality of images and a corresponding text comment that includes a plurality of segments;

retrieve, based on a pre-established key-word library, key word of each segment; and

match a segment, according to the key word retrieved from the segment, to a corresponding image(s) from the plurality of images.

10. The apparatus according to claim 9, wherein the processing circuitry is configured to:

select a key word matched to an image, based on the key-word library or all of the key words retrieved from the text comment, and label the image with the key word as a tag,

assign a segment as a candidate segment; and

determine, based on the tag of each image and the key word of the candidate segment, an image that corresponds to the candidate segment from the plurality of images.

11. The apparatus according to claim 10, wherein the processing circuitry is configured to identify an image, based on the key-word library or the key word retrieved from the text comments, to get image character,

select a key word when the image character identified from the image is matched with the key word,

and label the image with the key word as a tag.

12. The apparatus according to claim 10, wherein the processing circuitry is configured to:

calculate, based on the tag of an image and the key word of the candidate segment, a correlative-value of the image with the candidate segment; and

designate an image corresponded to the candidate segment when the correlative-value is higher than an predetermined value.

13. The apparatus according to claim 12, wherein the key-word library includes:

a first candidate word retrieved from another text comment that is different from the text comment about the plurality of images; and

a second candidate word retrieved from the tag of other image different with the plurality of images.

14. The apparatus according to claim 13, wherein the first candidate word and the second candidate word contain a word selected from a group consist of subject, scene, image metadata, positional relation between the plurality of images, a word with a frequency higher than a predetermined frequency of the text comment.

15. The apparatus according to claim 14, wherein each classification has a predetermined weight and a weighted number of the tags correlated to the candidate segment is calculated as the correlative-value of the image to the candidate segment.

16. The apparatus according to claim 9, wherein the processing circuitry is configured to obtain the text comment and segment the text comment into the plurality of segments by comma, semi-colon, period, or paragraph.

17. A non-transitory computer-readable storage medium including computer executable instructions, wherein the instructions, when executed by a computer, cause the computer to execute a process for matching text to images, the process comprising:

acquiring a plurality of images and corresponding text comments that includes a plurality of segments;

retrieving, based on a pre-established key-word library, a key word of each segment; and

matching a segment, according to the key word retrieved from the segment, to a corresponding image(s) from the plural images.