COMMODITY RECOGNITION APPARATUS AND COMMODITY RECOGNITION METHOD

• US 20150023555A1
• Filed: 07/14/2014
• Published: 01/22/2015
• Est. Priority Date: 07/19/2013
• Status: Abandoned Application

• Current Assignee: Toshiba Tec Corporation (Toshiba Corporation)
• Original Assignee: Toshiba Tec Corporation (Toshiba Corporation)
• Inventors: Okamura, Atsushi, Sugasawa, Hiroshi
• Application Number:
  US14/330,108
• Publication Number:
  US 20150023555A1
• Time in Patent Office: Days
• US Class Current: 382/103
• CPC Class Codes: G06F 18/214 Generating training patterns; Bootstrap methods, e.g. bagging or boosting
• CPC Class Codes: G06Q 20/208 Input by product or record sensing, e.g. weighing or scanner processing
• CPC Class Codes: G06V 10/774 Generating sets of training patterns; Bootstrap methods, e.g. bagging or boosting
• CPC Class Codes: G06V 20/68 Food, e.g. fruit or vegetables
• CPC Class Codes: G07G 1/0054 with control of supplementary check-parameters, e.g. weight or number of articles

Abstract

In accordance with one embodiment, a commodity recognition apparatus receives, if a commodity is recognized as candidate of a target commodity by a recognition module, a selection input of the target commodity from the candidate; then adds appearance feature amount data to the feature amount data stored in a recognition dictionary file in association with an item of the target commodity the selection input of which is received; and meanwhile, writes log data containing the date and time when the appearance feature amount data is added to the recognition dictionary file in a log storage section.

Claims

1. A commodity recognition apparatus comprising:

an extraction module configured to extract, from an image captured by an image capturing module, an appearance feature amount of a target commodity contained in the image;

a recognition module configured to compare the appearance feature amount data extracted by the extraction module with feature amount data of each commodity stored in a recognition dictionary file to recognize the target commodity;

a reception module configured to receive, if a commodity is recognized as candidate of the target commodity by the recognition module, a selection input of the target commodity from the candidate;

an adding module configured to add the appearance feature amount data extracted by the extraction module to the feature amount data stored in the recognition dictionary file in association with an item of the target commodity the selection input of which is received by the reception module; and

a log writing module configured to write log data containing the date and time when the appearance feature amount data is added to the recognition dictionary file by the adding module in a log storage section.

2. The commodity recognition apparatus according to claim 1, wherein

the log writing module includes a module which writes, when other feature amount data is deleted from the recognition dictionary file in response to the addition of the appearance feature amount data to the recognition dictionary file performed by the adding module, log data containing the date and time when other feature amount data is deleted in the log storage section.

3. The commodity recognition apparatus according to claim 1, further comprising:

an output module configured to visually output the log data stored in the log storage section.

4. The commodity recognition apparatus according to claim 3, further comprising:

a calculation module configured to calculate a correct recognition rate at which each commodity can be correctly recognized by the recognition module using the feature amount data of each commodity stored in the recognition dictionary file; and

a recognition rate writing module configured to write the correct recognition rate calculated by the calculation module in a recognition rate storage section together with the date and time when the correct recognition rate is calculated;

wherein

the output module visually outputs the correct recognition rate stored in the recognition rate storage section together with the closest date and time after the date and time contained in the log data in association with the log data.

5. The commodity recognition apparatus according to claim 1, further comprising:

a cutting out module configured to cut out, from an image captured by the image capturing module, the image of the target commodity contained in the image;

wherein

the log data written in the log storage section contains the image of the target commodity cut out by the cutting out module.

6. A commodity recognition method, including:

extracting, from an image captured by an image capturing module, an appearance feature amount of a target commodity contained in the image;

comparing the extracted appearance feature amount data with feature amount data of each commodity stored in a recognition dictionary file to recognize the target commodity;

receiving, if a commodity is recognized as candidate of the target commodity, a selection input of the target commodity from the candidate;

adding the extracted appearance feature amount data to the feature amount data stored in the recognition dictionary file in association with an item of the target commodity the selection input of which is received; and

writing log data containing the date and time when the appearance feature amount data is added to the recognition dictionary file in a log storage section.