SYSTEMS AND METHODS FOR CLASSIFYING OBJECTS IN DIGITAL IMAGES CAPTURED USING MOBILE DEVICES

• US 20170103281A1
• Filed: 12/20/2016
• Published: 04/13/2017
• Est. Priority Date: 03/13/2013
• Status: Active Grant

• Current Assignee: Kofax Incorporated
• Original Assignee: Kofax Incorporated
• Inventors: Amtrup, Jan W., Macciola, Anthony, Thompson, Steve, Ma, Jiyong, Shustorovich, Alexander, Thrasher, Christopher W.
• Granted Patent: US 10,127,441 B2
• Time in Patent Office: Days
• CPC Class Codes: G06F 18/2411 based on the proximity to a decision surface, e.g. support vector machines
• CPC Class Codes: G06V 10/247 by affine transforms, e.g. correction due to perspective effects; Quadrilaterals, e.g. trapezoids
• CPC Class Codes: G06V 20/62 Text, e.g. of license plates, overlay texts or captions on TV images
• CPC Class Codes: G06V 30/142 using hand-held instruments; Constructional details of the instruments
• CPC Class Codes: G06V 30/224 of printed characters having additional code marks or containing code marks
• CPC Class Codes: G06V 30/40 Document-oriented image-based pattern recognition
• CPC Class Codes: G06V 30/412 Layout analysis of documents structured with printed lines or input boxes, e.g. business forms or tables
• CPC Class Codes: G06V 30/413 Classification of content, e.g. text, photographs or tables
• CPC Class Codes: G06V 30/416 Extracting the logical structure, e.g. chapters, sections or page numbers; Identifying elements of the document, e.g. authors

Abstract

In one embodiment, a system includes: a processor; and logic in and/or executable by the processor to cause the processor to: generate a first feature vector based on a digital image captured by a mobile device; compare the first feature vector to a plurality of reference feature matrices; classify an object depicted in the digital image as a member of a particular object class based at least in part on the comparison; determine one or more object features of the object based at least in part on the particular object class; and detect one or more additional objects belonging to the particular object class based on the determined object feature(s). The one or more additional objects are depicted either in the digital image or another digital image received by the mobile device. Corresponding computer program products are also disclosed.

Claims

1. A system, comprising:

a processor; and

logic in and/or executable by the processor to cause the processor to;

generate a first feature vector based on a digital image captured by a mobile device;

compare the first feature vector to a plurality of reference feature matrices;

classify an object depicted in the digital image as a member of a particular object class based at least in part on the comparison;

determine one or more object features of the object based at least in part on the particular object class; and

detect one or more additional objects belonging to the particular object class based on the determined object feature(s),

wherein the one or more additional objects are depicted either in the digital image or another digital image received by the mobile device.

2. The system as recited in claim 1, wherein the one or more object features comprise an object color scheme;

and

wherein the system further comprises logic in and/or executable by the processor to cause the processor to binarize the digital image based at least in part on;

determining the object color scheme;

adjusting one or more binarization parameters based on the object color scheme; and

thresholding the digital image using the one or more adjusted binarization parameters.

3. The system as recited in claim 1, wherein the one or more object features comprise an object class mask;

and

wherein the system further comprises logic in and/or executable by the processor to cause the processor to binarize the digital image based at least in part on;

determining the object class mask;

applying the object class mask to the digital image; and

thresholding a subregion of the digital image based on the object class mask.

4. The system as recited in claim 3, wherein the one or more object features further comprise an object color scheme, and

wherein binarizing the digital image further comprises:

determining the object color scheme;

adjusting one or more binarization parameters based on the object color scheme; and

thresholding the digital image using the one or more adjusted binarization parameters.

5. The system as recited in claim 1, further comprising logic in and/or executable by the processor to cause the processor to:

generate a first representation of the digital image, the first representation being characterized by a reduced resolution,

wherein generating the first representation comprises;

dividing the digital image into a plurality of sections; and

determining, for each section, at least one characteristic value, each characteristic value corresponding to one or more features descriptive of the section; and

wherein the first feature vector is generated based on the first representation of the digital image.

6. The system as recited in claim 1, further comprising logic in and/or executable by the processor to cause the processor to:

define at least one hyperplane between at least some of the reference feature matrices, each hyperplane defining a boundary between first objects corresponding to one of the reference feature matrices and second objects corresponding to another of the reference feature matrices.

7. The system as recited in claim 1, wherein generating the first feature vector comprises determining a color profile of some or all of the object.

8. The system as recited in claim 1, further comprising logic in and/or executable by the processor to cause the processor to perform at least one of the following functions:

predict an identity of text depicted on the object using optical character recognition (OCR), wherein the prediction is based at least in part on the particular object class; and

modify at least one identity predicted using OCR based on an expected format of text depicted on the object, wherein the expected format is determined based at least in part on the particular object class.

9. The system as recited in claim 1, further comprising logic in and/or executable by the processor to cause the processor to:

determine a geographical location associated with the mobile device, wherein classifying the object is further based at least in part on the geographical location.

10. The system as recited in claim 1, further comprising logic in and/or executable by the processor to cause the processor to:

output an indication of the particular object class to a display of the mobile device; and

receive user input via the display of the mobile device in response to outputting the indication, the user input comprising either a confirmation, a negation, or a modification of the particular object class.

11. A computer program product comprising:

a computer readable storage medium having program code embodied therewith, the program code readable/executable by a processor to;

generate a first feature vector based on a digital image captured by a mobile device;

compare the first feature vector to a plurality of reference feature matrices;

classify an object depicted in the digital image as a member of a particular object class based at least in part on the comparison;

determine one or more object features of the object based at least in part on the particular object class; and

detect one or more additional objects belonging to the particular object class based on the determined object feature(s),

wherein the one or more additional objects are depicted either in the digital image or another digital image received by the mobile device.

12. The computer program product as recited in claim 11, wherein the one or more object features comprise an object color scheme;

and

wherein the computer program product further comprises program code readable/executable by the processor to binarize the digital image based at least in part on;

determining the object color scheme;

adjusting one or more binarization parameters based on the object color scheme; and

thresholding the digital image using the one or more adjusted binarization parameters.

13. The computer program product as recited in claim 11, wherein the one or more object features comprise an object class mask, and

wherein the computer program product further comprises program code readable/executable by the processor to binarize the digital image based at least in part on:

determining the object class mask;

applying the object class mask to the digital image; and

thresholding a subregion of the digital image based on the object class mask.

14. The computer program product as recited in claim 13, wherein the one or more object features further comprise an object color scheme, and

wherein binarizing the digital image further comprises:

determining the object color scheme;

adjusting one or more binarization parameters based on the object color scheme; and

thresholding the digital image using the one or more adjusted binarization parameters.

15. The computer program product as recited in claim 11, further comprising program code readable/executable by the processor to:

generate a first representation of the digital image, the first representation being characterized by a reduced resolution,

wherein generating the first representation comprises;

dividing the digital image into a plurality of sections; and

determining, for each section, at least one characteristic value, each characteristic value corresponding to one or more features descriptive of the section; and

wherein the first feature vector is generated based on the first representation of the digital image.

16. The computer program product as recited in claim 11, further comprising program code readable/executable by the processor to:

define at least one hyperplane between at least some of the reference feature matrices, each hyperplane defining a boundary between first objects corresponding to one of the reference feature matrices and second objects corresponding to another of the reference feature matrices.

17. The computer program product as recited in claim 11, wherein generating the first feature vector comprises determining a color profile of some or all of the object.

18. The computer program product as recited in claim 11, further comprising program code readable/executable by the processor to perform at least one of the following functions:

predict an identity of text depicted on the object using optical character recognition (OCR), wherein the prediction is based at least in part on the particular object class; and

modify at least one identity predicted using OCR based on an expected format of text depicted on the object, wherein the expected format is determined based at least in part on the particular object class.

19. The computer program product as recited in claim 11, further comprising program code readable/executable by the processor to:

determine a geographical location associated with the mobile device, wherein classifying the object is further based at least in part on the geographical location.

20. The computer program product as recited in claim 11, further comprising program code readable/executable by the processor to:

output an indication of the particular object class to a display of the mobile device; and

receive user input via the display of the mobile device in response to outputting the indication, the user input comprising either a confirmation, a negation, or a modification of the particular object class.