Methods and Systems for Identifying Text in Digital Images

• US 20110110596A1
• Filed: 01/17/2011
• Published: 05/12/2011
• Est. Priority Date: 09/06/2006
• Status: Active Grant

• Current Assignee: Sharp Kabushiki Kaisha (Hon Hai Precision Industry Co., Ltd.)
• Original Assignee: Sharp Kabushiki Kaisha (Hon Hai Precision Industry Co., Ltd.)
• Inventors: Matsuda, Toyohisa, Campbell, Richard John, Chen, Lawrence Shao-hsien
• Granted Patent: US 8,150,166 B2
• Time in Patent Office: Days
• US Class Current: 382/190
• CPC Class Codes: G06V 30/413 Classification of content, e.g. text, photographs or tables

Abstract

Aspects of the present invention relate to systems, methods and devices for detection of text in an image using an initial text classification result and a verification process.

Claims

1. A method for identifying text in a digital image, said method comprising:

receiving a first feature data set comprising measurements of a first feature on a digital image;

receiving a confidence data set related to said first feature data set, wherein said confidence data set indicates a confidence level of the measurements of said first feature data set;

receiving digital image data related to said digital image;

calculating a pictorial feature for said digital image data using said first feature data set and said confidence data set;

forming a pictorial confidence image using said pictorial feature and said first feature data set; and

generating a text-map based on said pictorial confidence image.

2. A method as described in claim 1 wherein said pictorial feature is masked entropy.

3. A method as described in claim 1 wherein said first feature is an edge feature.

4. A method as described in claim 1 wherein said digital image data is a luminance image.

5. A method as described in claim 1 wherein the resolution of said digital image data is less than the resolution of said first feature data set.

6. A method as described in claim 1 further comprising generating a mask from said first feature data set and said confidence data set.

7. A method as described in claim 1 wherein said forming a pictorial confidence image further comprises hysteresis thresholding.

8. A method as described in claim 1 wherein said forming a pictorial confidence image further comprises a plurality of scan passes.

9. A method as described in claim 8 wherein said number of scan passes is four.

10. A method as described in claim 1 wherein said pictorial confidence image and said first feature data set have the same resolution.