Cognitive image detection and recognition

• US 10,546,184 B2
• Filed: 06/19/2015
• Issued: 01/28/2020
• Est. Priority Date: 05/27/2014
• Status: Active Grant

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Dugan, Casey, Geyer, Werner
• Primary Examiner(s): Perlman, David
• Application Number:
  US14/744,058
• Publication Number:
  US 20150347826A1
• Time in Patent Office: 1,684 Days
• Field of Search: None
• CPC Class Codes: G06F 18/2155 characterised by the incorporation of unlabelled data, e.g. multiple instance learning [MIL], semi-supervised techniques using expectation-maximisation [EM] or naïve labelling
• CPC Class Codes: G06F 18/40 Software arrangements specially adapted for pattern recognition, e.g. user interfaces or toolboxes therefor
• CPC Class Codes: G06V 10/96 Management of image or video recognition tasks
• CPC Class Codes: G06V 40/161 Detection; Localisation; Normalisation
• CPC Class Codes: G06V 40/172 Classification, e.g. identification

Abstract

Embodiments are directed to an image processing station for associating a non-trusted data set with a trusted data set. The station includes a memory and a user interface configured to receive the trusted data set and the non-trusted data set. The station further includes a processor system communicatively coupled to the memory and the user interface. The processor system is configured to generate, based at least in part on processing the trusted data set and the non-trusted data set, a confidence value that represents a probability that at least a portion of the non-trusted data set identifies at least a portion of the trusted data set.

Claims

1. A computer implemented method configured to determine that a non-trusted data set is associated with a trusted data set, the computer implemented method comprising;

receiving, at a user interface of an image processing station, the non-trusted data set from a user;

capturing, at a trusted data source of the user interface, the trusted data set;

wherein the non-trusted data set received from the user has not been associated with the trusted data set;

wherein the trusted data set captured at the trusted data source of the user interface does not include the non-trusted data set;

receiving, at a processor system of the image processing station communicatively coupled to a memory and the user interface, the trusted data set and the non-trusted data set;

analyzing, using the processor system of the image processing station, the trusted data set and the non-trusted data set to determine one or more relationships between the trusted data set and the non-trusted data set; and

generating, using the processor system of the image processing station, based at least in part on an output from analyzing the trusted data set and the non-trusted data set to determine one or more relationships between the trusted data set and the non-trusted data set, a confidence value that represents a probability that at least a portion of the non-trusted data set identifies at least a portion of the trusted data set; and

making a determination that the trusted data set is associated with the non-trusted data set based at least in part on the confidence value;

wherein the computer implemented method assumes that the non-trusted data set is not associated with the trusted data set until the computer implemented method makes the determination that the trusted data set is associated with the non-trusted data set.

2. The computer implemented method of claim 1 further comprising:

storing in a first portion of the memory, based at least in part on an assessment of the confidence value, identified trusted data sets; and

storing in a second portion of the memory, based at least in part on the confidence value not exceeding a threshold, partially identified trusted data sets;

wherein, the identified trusted data sets comprise trusted data that has been determined to be identified by non-trusted data; and

wherein, the partially identified trusted data sets comprise trusted data that has not been determined to be identified by non-trusted data.

3. The computer implemented method of claim 2, wherein generating further comprises generating the confidence value based at least in part on:

at least one identified trusted data set previously generated by the processor system of the image processing station; and

at least one identified trusted data set generated by a first separate processor system of a first separate image processing station communicatively coupled to the image processing station through a network.

4. The computer implemented method of claim 3, wherein generating further comprises generating the confidence value based at least in part on:

at least one partially identified trusted data set previously generated by the processor system of the image processing station; and

at least one partially identified trusted data set generated by a second separate processor system of a second separate image processing station communicatively coupled to the image processing station through a network.

5. The computer implemented method of claim 1, wherein analyzing comprises applying data comparison operations and rule-based reasoning operations to the trusted data set and the non-trusted data set.