Detection of sky in digital color images

• US 7,336,819 B2
• Filed: 12/29/2003
• Issued: 02/26/2008
• Est. Priority Date: 12/29/2003
• Status: Expired due to Fees

• Current Assignee: Monument Peak Ventures, LLC (Dominion Harbor Enterprises, LLC)
• Original Assignee: Eastman Kodak Company
• Inventors: Luo, Jiebo, Gallagher, Andrew C., Hao, Wei
• Primary Examiner(s): Ahmed; Samir
• Assistant Examiner(s): Newman; Michael A
• Application Number:
  US10/747,597
• Publication Number:
  US 20050147298A1
• Time in Patent Office: 1,520 Days
• Field of Search: 382/163, 382/164, 382/165, 382/166, 382/173, 382/180, 382/224, 382/225, 382/226, 382/227, 382/228, 382/162
• US Class Current: 382/165
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/143 involving probabilistic approaches, e.g. Markov random field [MRF] modelling
• CPC Class Codes: G06T 7/90 Determination of colour characteristics
• CPC Class Codes: G06V 10/56 relating to colour
• CPC Class Codes: G06V 20/10 Terrestrial scenes scenes under surveillance with static cameras G06V20/52; scenes perceived from the exterior of a vehicle G06V20/56; scenes perceived from the interior of a vehicle G06V20/59

Abstract

A method of detecting sky in a digital color image having pixels is disclosed. The method includes identifying pixels from the digital color image representing an initial sky region; developing a model based on the identified sky pixels, wherein such model is a mathematical function that has inputs of pixel position and outputs of color; and using the model to operate on the digital color image to classify additional pixels not included in the initial sky region as sky.

Claims

1. A method of detecting sky in a digital color image having pixels, the method comprising:

a) identifying pixels having a range of colors from the digital color image and forming an initial sky region using the identified sky pixels;

b) developing a model based on the identified sky pixels, wherein such model is a mathematical function that has inputs of pixel position and outputs of color;

c) using the model to operate on the digital color image to classify additional pixels not included in the formed initial sky region as sky including;

i) determining a difference between the color of a pixel and the model estimated color for the pixel'"'"'s position;

ii) using the determined difference at a plurality of pixel positions to calculate a residual error from the differences; and

iii) using the difference to assign a probability that the pixel represents sky further, by computing a ratio of the difference with the residual error and using the ratio to assign the probability; and

d) using the probability to determine if the pixel is in a sky region.

2. The method of claim 1 wherein the model is a two-dimensional polynomial of the pixel position in the digital color image.

3. The method of claim 2 wherein the polynomial is a second-order polynomial.

4. The method of claim 1 wherein the step of identifying an initial sky region further comprises:

i) extracting connected components of said potential sky pixels;

ii) eliminating ones of said connected components that have a texture above a predetermined texture threshold; and

iii) computing desaturation gradients of said connected components; and

comparing said desaturation gradients of said connected components with a predetermined desaturation gradient for sky to identify true sky regions in said digital color image.

5. The method of claim 1 wherein in computing the probability of the pixels as sky further comprises:

computing a color feature, related to the “

blueness”

of the pixels in the region; and

using the color feature to determine if the pixels are not sky.