SYSTEM AND METHOD FOR IDENTIFYING AND CLASSIFYING COLOR REGIONS FROM A DIGITAL IMAGE

• US 20080253647A1
• Filed: 04/14/2008
• Published: 10/16/2008
• Est. Priority Date: 04/13/2007
• Status: Active Grant

• Current Assignee: Kofax Incorporated
• Original Assignee: Kofax Incorporated
• Inventors: Cho, Seungyeon, Bither, William
• Granted Patent: US 8,244,031 B2
• Time in Patent Office: Days
• US Class Current: 382/164
• CPC Class Codes: G06V 30/10 Character recognition
• CPC Class Codes: G06V 30/18105 related to colour
• CPC Class Codes: G06V 30/413 Classification of content, e.g. text, photographs or tables

Abstract

A system and method of identifying and classifying regions of a digital image. The method includes an initial step of inputting an image as a color digital image. Subsequently, information that identifies color regions of the color digital image is obtained. Finally, color and non-color regions of the color digital image are classified based upon the identifying information.

Claims

1. A method of identifying and classifying regions of a digital image, said method comprising the steps of:

inputting an image as a color digital image;

obtaining information that identifies color regions of said color digital image; and

classifying color and non-color regions of said color digital image based upon said identifying information.

2. The method of claim 1 including the step of:

obtaining information that identifies photo regions of said color digital image.

3. The method of claim 2 wherein the step of:

classifying said color and non-color regions also includes classifying said photo regions based upon said identifying information.

4. The method of claim 1 including the step of:

individually compressing said color and non-color regions based on a quality characteristic of said region.

5. The method of claim 4 including the step of:

compiling said compressed regions;

wherein said compilation results in a size and readability optimized file.

6. A method of identifying and classifying regions of a digital image, said method comprising the steps of:

inputting an image as a color digital image;

obtaining information that identifies color and photo regions of said color digital image;

classifying color, photo, non-color and non-photo regions of said color digital image based upon said identifying information; and

individually compressing said color, non-color, photo and non-photo regions based on a quality characteristic of each of said regions.

7. The method of claim 6 wherein said photo regions are classified by the following steps:

transforming said color digital image to gray scale;

applying a first median filtering method to said gray scale image creating a first filtered image;

applying a second median filtering method to said gray scale image creating a second filtered image;

creating a difference image from between said first and second filtered images;

converting said difference image to a binary image;

obtaining a set of bounding boxes of black pixels in said binary image through a connected components method; and

applying a size analysis to said connected components wherein connected components having a size below a predetermined threshold are marked as non-photo regions and remaining bounding boxes of said connected components are photo regions.

8. The method of claim 6 including the steps of:

assessing a bit-depth of said color digital image to determine whether said image is entirely black and white or entirely grayscale; and

terminating said classification of said regions if said image has a bit-depth indicating that it is black and white or grayscale.

9. The method of claim 6 including the step of:

resampling and resizing said image to expedite the identification and classification of said regions of said digital image.

10. The method of claim 6 including the steps of:

identifying black border regions in said image;

removing any identified black border regions.

11. The method of claim 10 wherein said identification of black border elements includes the steps of:

determining whether pixels that comprise said color digital image are black;

scanning said black pixels along a dimension of said image to determine a boundary of said black border;

establishing said boundary of said black border where said non-black pixels exceed one-percent of a total of said pixels of said scanned dimension.

12. The method of claim 6 including the steps of:

identifying gray elements in said image;

removing any identified gray elements.

13. The method of claim 12 wherein identifying gray elements includes:

transforming said color digital image to gray scale to create a gray scale image;

computing a Malahanobis distance for each color pixel in said color digital image to a corresponding pixel of said transformed gray scale image; and

marking a pixel in said color digital image as gray if it exceeds a predetermined distance from its counterpart in said gray scale image.

14. The method of claim 12 wherein said identification of color elements includes the following:

creating a binary image from said color digital image;

marking any pixels previously identified as gray or photo elements as white and any remaining pixels as black;

applying a connected components method to obtain bounding boxes of connected components of said black pixels;

merging any overlapping bounding boxes into a single bounding box;

applying a size analysis method to said bounding boxes in which connected components having a bounding box of a smaller size than a predetermined value are marked as non-color and a remaining set of bounding boxes of said connected components are marked as a color region.

15. The method of claim 6 including the steps of:

identifying background elements;

removing said background elements.

16. The method of claim 15 wherein identifying background elements includes:

creating a memory space having a width and height corresponding to that of said color digital image;

applying an HSL color transformation to said color digital image;

copying an H component from said HSL transformation for each pixel of said color digital image into said memory space;

applying an unsupervised clustering method to said H component data to identify background colors if present;

applying an image slicing method to said H component data to obtain a binary image in which background pixels are black;

obtaining a set of bounding boxes of using a connected components methodology for said black pixels; and

applying a size analysis to determine which bounding boxes are to be merged and considered background.

17. The method of claim 6 including the step of:

merging said photo and said color regions.

18. The method of claim 9 including the step of:

restoring said image to its original size prior to said resampling.

19. Electronically-readable media tangibly embodying a program of instructions executable by a processor to perform a method of digital image analysis, the method comprising the steps of:

inputting an image as a color digital image;

obtaining information that identifies color regions of said color digital image; and

classifying color and non-color regions of said color digital image based upon said identifying information.

20. A digital imaging system comprising:

a color image capturing device configured for obtaining a digital image; and

a processor electrically connected to at least one of the image capturing device configured for obtaining information that identifies color regions of said color digital image and classifying color and non-color regions of said color digital image based upon said identifying information.