Image segmentation using template prediction

• US 20060056689A1
• Filed: 10/28/2003
• Published: 03/16/2006
• Est. Priority Date: 11/19/2002
• Status: Abandoned Application

• Current Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Original Assignee: Koninklijke Philips Electronics N.V. (Koninklijke Philips N.V.)
• Inventors: De Haan, Gerard, Wittebrood, Rimmert B
• Application Number:
  US10/535,059
• Publication Number:
  US 20060056689A1
• Time in Patent Office: Days
• US Class Current: 382/173
• CPC Class Codes: G06T 2207/10016 Video; Image sequence
• CPC Class Codes: G06T 2207/20021 Dividing image into blocks, subimages or windows
• CPC Class Codes: G06T 7/11 Region-based segmentation

Abstract

The invention relates to image segmentation using templates and spatial prediction. The templates of neighboring pixels are used for predicting the features of a current pixel. The pixel is assigned to the segments of neighboring pixels according to the deviation of its features from the templates.

Claims

1. Method for segmenting images into groups of segments, said segments being based on image features, with the steps of:

a) determining a group of pixels for segmenting,

b) determining for said group feature characteristics,

c) determining from neighboring groups segment templates, said segment templates describing constant or continuous features within said neighboring groups,

d) calculating for said group error values by comparing features of said group with features of said segment templates, and

e) deciding to assign said group to one of said segment templates, or to create a new segment template based on said error values.

2. Method according to claim 1, with the steps of determining for said image a plurality of groups and carrying out the steps a)-e) for all groups of said image.

3. Method according to claim 1, characterized in that said segment templates are determined spatially and/or temporally.

4. Method according to claim 1, characterized in that scanning said groups of pixels for said segmentation is done memory matched.

5. Method according to claim 1, characterized in that said decision to assign said group to one of said segment templates, or to a newly created segment template is based on threshold values.

6. Method according to claim 1, characterized in that said features are based on chrominance, and/or luminance values, statistical derivatives of pixels, histograms, co-occurrence matrices and/or fractal dimensions.

7. Method according to claim 1, characterized in that said segment templates comprise an average luminance and chrominance span of said pixels.

8. Method according to claim 2, characterized in that said segment templates comprise at least one histogram.

9. Method according to claim 3, characterized in that said segment templates comprise motion models.

10. Method according to claim 1, characterized in that said segment templates comprise image position information.

11. Device for calculating image segmentation according to claim 1 comprising:

grouping means for grouping pixels of images into groups,

extracting means for extracting feature characteristics from said groups,

storing means for storing segment templates of neighboring groups,

comparing means for comparing said extracted features with features of said segment templates,

decision means for assigning said group of pixels to one of said segment templates or to create a new segment template based on error values determined between said extracted features and features of said segment templates.

12. Use of a method according to claim 1 in image and/or video processing, medical image processing, crop analysis, video compression, motion estimation, weather analysis, fabrication monitoring, and/or intrusion detection.