Barcode Photo-image Processing System

• US 20130153662A1
• Filed: 06/26/2012
• Published: 06/20/2013
• Est. Priority Date: 12/19/2011
• Status: Abandoned Application

• Current Assignee: Mindtree Limited (Larsen & Toubro Limited)
• Original Assignee: Mindtree Limited (Larsen & Toubro Limited)
• Inventors: Narasa Prakash, Suma
• Application Number:
  US13/532,794
• Publication Number:
  US 20130153662A1
• Time in Patent Office: Days
• US Class Current: 235/462.07
• CPC Class Codes: G06K 7/1486 Setting the threshold-width for bar codes to be decoded

Abstract

A computer implemented method and system for processing a low quality captured image of a barcode of any type having a large amount of data is provided. An image processing application on a computing device acquires the captured image of the barcode, determines the type, for example, format, shape, etc., of the barcode in the acquired image of the barcode, and creates a gray barcode image from the acquired image of the barcode by gray shading over an entirety of the acquired image of the barcode. The image processing application modularizes the created gray barcode image based on the type of the barcode and binarizes the created gray barcode image based on the type of the barcode by comparing an average gray level intensity of each of multiple grids of pixels or by comparing gray level intensities of individual pixels in the created gray barcode image, with a predetermined threshold.

Claims

1. A computer implemented method for processing a captured image of a barcode, said method employing a computer system comprising at least one processor communicatively coupled to a non-transitory computer readable storage medium that stores instructions executable by said at least one processor, said at least one processor configured to implement said method, said method comprising:

providing an image processing application on a computing device;

acquiring said captured image of said barcode by said image processing application, wherein said barcode is of a plurality of types and comprises a large amount of data, and wherein said captured image of said barcode is of low quality;

determining a type of said barcode in said acquired image of said barcode by said image processing application;

creating a gray barcode image from said acquired image of said barcode by said image processing application, by gray shading over an entirety of said acquired image of said barcode;

modularizing said created gray barcode image by said image processing application based on said determined type of said barcode; and

binarizing said created gray barcode image by said image processing application based on said determined type of said barcode by one of comparing an average gray level intensity of each of a plurality of grids of pixels in said created gray barcode image and comparing a gray level intensity of each of individual pixels in said created gray barcode image, with a predetermined threshold.

2. The computer implemented method of claim 1, further comprising scaling said entirety of said acquired image of said barcode by said image processing application to create a scaled barcode image prior to said creation of said gray barcode image, wherein said gray barcode image is created by gray shading over an entirety of said scaled barcode image.

3. The computer implemented method of claim 1, further comprising computing said gray level intensity of said each of said individual pixels in said created gray barcode image and comparing said computed gray level intensity with said predetermined threshold based on said determined type of said barcode by said image processing application, wherein said created gray barcode image is binarized by said image processing application based on said comparison of said computed gray level intensity of said each of said individual pixels in said created gray barcode image with said predetermined threshold depending on said determined type of said barcode.

4. The computer implemented method of claim 1, further comprising computing said average gray level intensity of each of said grids of said pixels in said created gray barcode image and comparing said computed average gray level intensity with said predetermined threshold based on said determined type of said barcode by said image processing application, wherein said created gray barcode image is binarized by said image processing application based on said comparison of said computed average gray level intensity of said each of said grids of said pixels in said created gray barcode image with said predetermined threshold depending on said determined type of said barcode.

5. The computer implemented method of claim 1, further comprising configuring a grid size for said modularization of said created gray barcode image based on predetermined criteria by said image processing application.

6. The computer implemented method of claim 1, wherein said captured image of said barcode is of said low quality with respect to image resolution, noise, and distortion.

7. The computer implemented method of claim 1, wherein said data in said barcode comprises one or more of textual content, image content, graphical content, and any combination thereof.

8. The computer implemented method of claim 1, wherein said type of said barcode comprises one of a shape of said barcode, a format of said barcode, and a combination thereof.

9. The computer implemented method of claim 8, wherein said shape of said barcode is one of a linear shape and a quadra-shape.

10. The computer implemented method of claim 8, wherein said format of said barcode is one of a one-dimensional barcode format and a two-dimensional barcode format.

11. The computer implemented method of claim 1, wherein said modularization of said created gray barcode image by said image processing application is performed when said determined type of said barcode is of a quadra-shape.

12. The computer implemented method of claim 1, wherein said image processing application binarizes said modularized gray barcode image when said determined type of said barcode is of a quadra-shape.

13. The computer implemented method of claim 1, wherein said image processing application binarizes said created gray barcode image when said determined type of said barcode is of a linear shape.

14. The computer implemented method of claim 1, further comprising preserving a rest zone around said barcode by said image processing application during said modularization and said binarization of said created gray barcode image over said entirety of said created gray barcode image.

15. The computer implemented method of claim 1, further comprising preserving start points and end points of said barcode by said image processing application during said modularization and said binarization of said created gray barcode image over said entirety of said created gray barcode image.

16. The computer implemented method of claim 1, further comprising retaining a format and a shape of said barcode by said image processing application for reducing distortion of said format and said shape of said barcode.

17. The computer implemented method of claim 1, further comprising retaining said large amount of said data in said barcode by said image processing application for preventing corruption of said large amount of said data in said barcode.

18. A computer implemented system for processing a captured image of a barcode, said computer implemented system comprising:

at least one processor;

a non-transitory computer readable storage medium communicatively coupled to said at least one processor, said non-transitory computer readable storage medium storing modules of an image processing application of said computer implemented system that are executable by said at least one processor, said image processing application comprising;

an image acquisition module that acquires said captured image of said barcode, wherein said barcode is of a plurality of types and comprises a large amount of data, and wherein said captured image of said barcode is of low quality;

a barcode type determination module that determines a type of said barcode in said acquired image of said barcode;

a gray barcode creation module that creates a gray barcode image from said acquired image of said barcode, by gray shading over an entirety of said acquired image of said barcode;

a modularization module that modularizes said created gray barcode image based on said determined type of said barcode; and

a binarization module that binarizes said created gray barcode image based on said determined type of said barcode by one of comparing an average gray level intensity of each of a plurality of grids of pixels in said created gray barcode image and comparing a gray level intensity of each of individual pixels in said created gray barcode image, with a predetermined threshold.

19. The computer implemented system of claim 18, wherein said image processing application further comprises a scaling module that scales said entirety of said acquired image of said barcode to create a scaled barcode image prior to said creation of said gray barcode image, wherein said gray barcode creation module creates said gray barcode image by gray shading over an entirety of said scaled barcode image.

20. The computer implemented system of claim 18, wherein said image processing application further comprises a gray level intensity computation module that computes said gray level intensity of said each of said individual pixels in said created gray barcode image, and compares said computed gray level intensity with said predetermined threshold based on said determined type of said barcode, wherein said binarization module binarizes said created gray barcode image based on said comparison of said computed gray level intensity of said each of said individual pixels in said created gray barcode image with said predetermined threshold depending on said determined type of said barcode.

21. The computer implemented system of claim 20, wherein said gray level intensity computation module computes an average gray level intensity of each of said grids of said pixels in said created gray barcode image and compares said computed average gray level intensity with said predetermined threshold based on said determined type of said barcode, wherein said binarization module binarizes said created gray barcode image based on said comparison of said computed average gray level intensity of said each of said grids of said pixels in said created gray barcode image with said predetermined threshold depending on said determined type of said barcode.

22. The computer implemented system of claim 18, wherein said image processing application further comprises a grid size configuration module that configures a grid size for said modularization of said created gray barcode image based on predetermined criteria.

23. The computer implemented system of claim 18, wherein said captured image of said barcode is of said low quality with respect to image resolution, noise, and distortion.

24. The computer implemented system of claim 18, wherein said data in said barcode comprises one or more of textual content, image content, graphical content, and any combination thereof.

25. The computer implemented system of claim 18, wherein said type of said barcode comprises one of a shape of said barcode, a format of said barcode, and a combination thereof, wherein said shape of said barcode is one of a linear shape and a quadra-shape, and wherein said format of said barcode is one of a one-dimensional barcode format and a two-dimensional barcode format.

26. The computer implemented system of claim 18, wherein said modularization module modularizes said created gray barcode image when said determined type of said barcode is of a quadra-shape.

27. The computer implemented system of claim 18, wherein said binarization module binarizes said modularized gray barcode image when said determined type of said barcode is of a quadra-shape, and wherein said binarization module binarizes said created gray barcode image when said determined type of said barcode is of a linear shape.

28. The computer implemented system of claim 18, wherein said image processing application further comprises a barcode maintenance module that performs:

preserving a rest zone around said barcode during said modularization and said binarization of said created gray barcode image over said entirety of said created gray barcode image;

preserving start points and end points of said barcode during said modularization and said binarization of said created gray barcode image over said entirety of said created gray barcode image;

retaining a format and a shape of said barcode for reducing distortion of said format and said shape of said barcode; and

retaining said large amount of said data in said barcode for preventing corruption of said large amount of said data in said barcode.

29. A computer program product comprising a non-transitory computer readable storage medium, said non-transitory computer readable storage medium storing computer program codes comprising instructions executable by at least one processor, said computer program codes comprising:

a first computer program code for acquiring a captured image of a barcode, wherein said barcode is of a plurality of types and comprises a large amount of data, and wherein said captured image of said barcode is of low quality;

a second computer program code for determining a type of said barcode in said acquired image of said barcode;

a third computer program code for creating a gray barcode image from said acquired image of said barcode, by gray shading over an entirety of said acquired image of said barcode;

a fourth computer program code for modularizing said created gray barcode image based on said determined type of said barcode; and

a fifth computer program code for binarizing said created gray barcode image based on said determined type of said barcode by comparing one of a computed average gray level intensity of each of a plurality of grids of pixels in said created gray barcode image and a computed gray level intensity of each of said pixels in said created gray barcode image with said predetermined threshold depending on said determined type of said barcode.

30. The computer program product of claim 29, further comprising a sixth computer program code for scaling said entirety of said acquired image of said barcode to create a scaled barcode image prior to said creation of said gray barcode image, wherein said third computer program code performs said gray shading over an entirety of said scaled barcode image.