Content based on-device image adjustment

Patent metadata

Field	Value
Publication number	US-2023118072-A1
Application number	US-202117505105-A
Country	US
Kind code	A1
Filing date	Oct 19, 2021
Priority date	Oct 19, 2021
Publication date	Apr 20, 2023
Grant date	—

Abstract

Using a trained image classification model, a first image captured using an image capture device is classified, the trained image classification model executing in the same system as the image capture device, the classifying producing an inappropriate content classification of the first image. Using a trained feature extraction model, a pattern within a portion of the first image is recognized from the first image, the trained feature extraction model executing in the same system as the image capture device, the pattern predefined as inappropriate content. Based on the classification and the pattern, the first image is adjusted.

First claim

What is claimed is:

1 . A computer-implemented method comprising:
classifying, using a trained image classification model, a first image captured using an image capture device, the trained image classification model executing in the same system as the image capture device, the classifying producing an inappropriate content classification of the first image; recognizing, from the first image using a trained feature extraction model, a pattern within a portion of the first image, the trained feature extraction model executing in the same system as the image capture device, the pattern predefined as inappropriate content; and adjusting, based on the classification and the pattern, the first image.

2 . The computer-implemented method of claim 1 , wherein the classifying and the recognizing are performed concurrently.

3 . The computer-implemented method of claim 1 , further comprising:
classifying, using the trained image classification model, a second image captured using the image capture device, the classifying producing an inappropriate content classification of the second image; and adjusting, based on the classification of the second image, the second image.

4 . The computer-implemented method of claim 1 , wherein the classifying further produces a classification confidence score corresponding to the inappropriate content classification of the first image.

5 . The computer-implemented method of claim 4 , wherein the adjusting is performed responsive to determining that the classification confidence score is above a first confidence threshold.

6 . The computer-implemented method of claim 1 , wherein the recognizing further produces a recognition confidence score corresponding to recognition of the pattern.

7 . The computer-implemented method of claim 6 , wherein the adjusting is performed responsive to determining that the recognition confidence score is above a second confidence threshold.

8 . The computer-implemented method of claim 1 , wherein the adjusting is performed responsive to determining that a combined confidence score is above a third confidence threshold, the combined confidence score comprising a product of a classification confidence score corresponding to the inappropriate content classification of the first image and a recognition confidence score corresponding to recognition of the pattern.

9 . A computer program product for content based on-device image adjustment, the computer program product comprising:
one or more computer readable storage media, and program instructions collectively stored on the one or more computer readable storage media, the stored program instructions comprising: program instructions to classify, using a trained image classification model, a first image captured using an image capture device, the trained image classification model executing in the same system as the image capture device, the classifying producing an inappropriate content classification of the first image; program instructions to recognize, from the first image using a trained feature extraction model, a pattern within a portion of the first image, the trained feature extraction model executing in the same system as the image capture device, the pattern predefined as inappropriate content; and program instructions to adjust, based on the classification and the pattern, the first image.

10 . The computer program product of claim 9 , wherein the classifying and the recognizing are performed concurrently.

11 . The computer program product of claim 9 , the stored program instructions further comprising:
program instructions to classify, using the trained image classification model, a second image captured using the image capture device, the classifying producing an inappropriate content classification of the second image; and program instructions to adjust, based on the classification of the second image, the second image.

12 . The computer program product of claim 9 , wherein the classifying further produces a classification confidence score corresponding to the inappropriate content classification of the first image.

13 . The computer program product of claim 12 , wherein the adjusting is performed responsive to determining that the classification confidence score is above a first confidence threshold.

14 . The computer program product of claim 9 , wherein the recognizing further produces a recognition confidence score corresponding to recognition of the pattern.

15 . The computer program product of claim 14 , wherein the adjusting is performed responsive to determining that the recognition confidence score is above a second confidence threshold.

16 . The computer program product of claim 9 , wherein the adjusting is performed responsive to determining that a combined confidence score is above a third confidence threshold, the combined confidence score comprising a product of a classification confidence score corresponding to the inappropriate content classification of the first image and a recognition confidence score corresponding to recognition of the pattern.

17 . The computer program product of claim 9 , wherein the stored program instructions are stored in the at least one of the one or more storage media of a local data processing system, and wherein the stored program instructions are transferred over a network from a remote data processing system.

18 . The computer program product of claim 9 , wherein the stored program instructions are stored in the at least one of the one or more storage media of a server data processing system, and wherein the stored program instructions are downloaded over a network to a remote data processing system for use in a computer readable storage device associated with the remote data processing system.

19 . The computer program product of claim 9 , wherein the computer program product is provided as a service in a cloud environment.

20 . A computer system comprising one or more processors, one or more computer-readable memories, and one or more computer-readable storage media, and program instructions stored on at least one of the one or more storage media for execution by at least one of the one or more processors via at least one of the one or more memories, the stored program instructions comprising:
program instructions to classify, using a trained image classification model, a first image captured using an image capture device, the trained image classification model executing in the same system as the image capture device, the classifying producing an inappropriate content classification of the first image; program instructions to recognize, from the first image using a trained feature extraction model, a pattern within a portion of the first image, the trained feature extraction model executing in the same system as the image capture device, the pattern predefined as inappropriate content; and program instructions to adjust, based on the classification and the pattern, the first image.

Assignees

• IBM

Inventors

• Pascal Geoffrey
• Menichetti Christophe
• Tallet Nicolas
• Vezolle Pascal

Classifications

• G06V20/35 Primary

  Categorising the entire scene, e.g. birthday party or wedding scene · CPC title

• G06V10/764

  using classification, e.g. of video objects · CPC title

• G06V10/82

  using neural networks · CPC title

• G06F18/214

  Generating training patterns; Bootstrap methods, e.g. bagging or boosting · CPC title

• G06F18/2411 Primary

  based on the proximity to a decision surface, e.g. support vector machines · CPC title