IMAGE COMPOSITION EVALUATING APPARATUS, INFORMATION PROCESSING APPARATUS AND METHODS THEREOF

• US 20150036921A1
• Filed: 07/31/2014
• Published: 02/05/2015
• Est. Priority Date: 08/02/2013
• Status: Active Grant

• Current Assignee: Canon Kabushiki Kaisha (Canon Inc.)
• Original Assignee: Canon Kabushiki Kaisha (Canon Inc.)
• Inventors: Jiang, Yong, Wu, Bo, Li, Xian, Lu, You
• Granted Patent: US 10,204,271 B2
• Time in Patent Office: Days
• US Class Current: 382/159
• CPC Class Codes: G06T 2207/20021 Dividing image into blocks, subimages or windows
• CPC Class Codes: G06T 2207/20084 Artificial neural networks [ANN]
• CPC Class Codes: G06T 2207/30168 Image quality inspection
• CPC Class Codes: G06T 7/0002 Inspection of images, e.g. flaw detection
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/187 involving region growing; involving region merging; involving connected component labelling
• CPC Class Codes: G06V 20/10 Terrestrial scenes scenes under surveillance with static cameras G06V20/52; scenes perceived from the exterior of a vehicle G06V20/56; scenes perceived from the interior of a vehicle G06V20/59

Abstract

The present invention discloses an image composition evaluating apparatus, an information processing apparatus and methods thereof. The image composition evaluating apparatus comprises: a region segmentation unit configured to segment an image into a plurality of regions; a region attribution extraction unit configured to extract at least one attribution from each of the regions; a region relationship description unit configured to describe relationships among the regions based on the extracted attributions; and a composition evaluation unit configured to evaluate the composition of the image based on the extracted attributions, the described relationships and at least one preset criterion. The present invention can evaluate more kinds of images and/or more kinds of composition problems.

Claims

1. An apparatus for evaluating image composition comprising:

a region segmentation unit configured to segment an image into a plurality of regions;

a region attribution extraction unit configured to extract at least one attribution from each of the regions;

a region relationship description unit configured to describe relationships among the regions based on the extracted attributions; and

a composition evaluation unit configured to evaluate the composition of the image based on the extracted attributions, the described relationships and at least one preset criterion.

2. The apparatus according to claim 1, wherein an over-segmentation method is employed to segment the image into the plurality of regions in the region segmentation unit.

3. The apparatus according to claim 2, wherein the over-segmentation method is a Felzenszwalb method or an SLIC method.

4. The apparatus according to claim 1, wherein the region attribution extraction unit further comprises the following units:

a region feature extraction unit configured to extract at least one feature from each of the regions;

a region classification unit configured to classify each of the regions into a preset class based on the extracted at least one feature and a trained model; and

a region attribution collection unit configured to collect the at least one attribution for each of the regions.

5. The apparatus according to claim 4, wherein a Recursive Neural Network method is employed to classify each of the regions into the preset class in the region classification unit.

6. The apparatus according to claim 4, wherein the region attribution extraction unit further comprises the following unit:

a region updating unit configured to merge isolated regions and to update the attributions of the regions after collecting the at least one attribution for each of the regions.

7. The apparatus according to claim 6, wherein the region updating unit further smoothes borders between the regions after merging isolated regions and before updating the attributions of the regions.

8. The apparatus according to claim 6, wherein when updating the attributions of the regions in the region updating unit, if a plurality of regions merged into one region have more than one class, the class for the one merged region is the one that most of the plurality of regions have.

9. The apparatus according to claim 1, wherein the region relationship description unit further comprises at least one of the following units:

a relative position calculating unit configured to calculate relative positions of the regions based on distances, neighbourhood and symmetries; and

a coordination degree calculating unit configured to calculate coordinate degrees among the regions based on relative area proportions, color matching and region complexity.

10. The apparatus according to claim 1, wherein the composition evaluation unit can find locations and reasons for composition problems in the image with respect to the at least one preset criterion.

11. The apparatus according to claim 1, further comprising the following unit:

a composition problem informing unit configured to output and inform evaluated composition problems after evaluating the composition of the image based on the extracted attributions, the described relationships and at least one preset criterion.

12. The apparatus according to claim 1, wherein the image is a photographic image.

13. The apparatus according to claim 1, wherein the extracted attributions and the described relationships depend on the at least one preset criterion.

14. The apparatus according to claim 1, wherein the extracted attributions comprise at least one of class, position, size, color and texture.

15. The apparatus according to claim 1, wherein the described relationships comprise at least one of relative position, relative area proportion, color matching and texture matching.

16. The apparatus according to claim 1, wherein the at least one preset criterion comprises at least one of object on head, area size judgement, major object position judgement, kissing border, close to border, middle separation and color matching.

17. A method for evaluating image composition comprising:

segmenting an image into a plurality of regions;

extracting at least one attribution from each of the regions;

describing relationships among the regions based on the extracted attributions; and

evaluating the composition of the image based on the extracted attributions, the described relationships and at least one preset criterion.

18. An information processing method, comprising the method for evaluating image composition according to claim 17.