System and method to automatically discriminate between different data types

Patent metadata

Field	Value
Publication number	US-9679168-B2
Application number	US-201615131069-A
Country	US
Kind code	B2
Filing date	Apr 18, 2016
Priority date	Oct 5, 2004
Publication date	Jun 13, 2017
Grant date	Jun 13, 2017

Abstract

There is described a system and method for automatically discriminating between different types of data with an image reader. In brief overview of one embodiment, the automatic discrimination feature of the present image reader allows a human operator to aim a hand held image reader at a target that can contain a dataform and actuate the image reader. An autodiscrimination module in the image reader in one embodiment analyzes image data representative of the target and determines a type of data represented in the image data.

First claim

The invention claimed is:

1. A method, comprising:
collecting image data from an object utilizing a two-dimensional image sensor;
analyzing, with a processor communicatively connected to the two-dimensional image sensor, the image data for a presence of curved elements to automatically discriminate between a dataform and a signature; and
outputting, with the processor, data indicative of the results of the analyzing.

2. The method according to claim 1 , wherein outputting data indicative of the results of the analyzing comprises outputting, with the processor, decoded barcode data.

3. The method according to claim 1 , wherein outputting data indicative of the results of the analyzing comprises outputting, with the processor, signature data.

4. The method according to claim 1 , comprising:
attempting to decode, with the processor, the image data as dataform data; and
testing, with the processor, the image data for characteristics indicative of a signature, if the attempt to decode the image data as dataform data fails.

5. The method according to claim 4 , wherein the attempt to decode the image data as dataform data comprises an attempt to decode the image data as a one dimensional bar code.

6. The method according to claim 5 , wherein the one dimensional bar code is a UPC bar code.

7. The method according to claim 1 , comprising:
attempting to decode, with the processor, the image data as dataform data;
testing, with the processor, the image data for characteristics indicative of a signature;
outputting, with the processor, decoded dataform data if the attempt to decode the image data as dataform data is successful; and
outputting, with the processor, signature data if the test for characteristics indicative of a signature is successful.

8. The method of claim 1 , wherein analyzing the image data for the presence of curved elements comprises utilizing a curvelet detector map.

9. An image reader comprising:
an image collection module for collecting images; and
a processor module configured for:
identifying a dataform in a first collected image collected by the image collection module;
identifying a signature in the first collected image;
processing the first collected image in an attempt to decode the dataform; and
if the dataform is decoded, outputting the decoded dataform.

10. The image reader of claim 9 , wherein the dataform is a barcode.

11. The image reader of claim 9 , comprising memory, wherein the processor module is configured for storing the identified signature in the memory.

12. The image reader of claim 9 , wherein the processor module is configured for identifying facial images in collected images.

13. The image reader of claim 9 , wherein the processor module is configured for identifying finger prints in collected images.

14. The image reader of claim 9 , wherein the processor module is configured for identifying printed text in collected images.

15. The image reader of claim 9 , wherein the processor module is configured for:
segmenting the first collected image into a plurality of regions;
determining which of the plurality of regions includes the dataform;
classifying the region including the dataform as a dataform region;
determining which of the plurality of regions includes the signature; and
classifying the region including the signature as a signature region.

16. An image reader comprising:
an image collection module for collecting images; and
a processor module configured for automatically distinguishing data types by:
segmenting a first collected image collected by the image collection module into a plurality of regions;
determining which of the plurality of regions includes a dataform;
classifying each region including a dataform as a dataform region;
determining which of the plurality of regions includes a signature; and
classifying each region including a signature as a signature region.

17. The image reader of claim 16 , wherein the processor module is configured for identifying barcodes in collected images.

18. The image reader of claim 16 , comprising memory, wherein the processor module is configured for:
identifying signatures in collected images; and
storing an identified signature in the memory.

19. The image reader of claim 16 , wherein the processor module is configured for identifying facial images in collected images.

20. The image reader of claim 16 , wherein the processor module is configured for identifying finger prints in collected images.

Assignees

• Hand Held Prod Inc

Inventors

• Wang Ynjiun

Classifications

• G06K7/10 Primary

  by electromagnetic radiation, e.g. optical sensing; by corpuscular radiation · CPC title

• G06K7/10881

  constructional details of hand-held scanners · CPC title

• G06K7/10722

  Photodetector array or CCD scanning · CPC title

• G06K7/0004 Primary

  Hybrid readers · CPC title

• G07C2209/41

  with means for the generation of identity documents · CPC title