System for identifying objects and features in an image

• US 6,151,424 A
• Filed: 09/09/1996
• Issued: 11/21/2000
• Est. Priority Date: 04/28/1994
• Status: Expired due to Term

• Current Assignee: Shin-Yi Hsu
• Original Assignee: Shin-Yi Hsu
• Inventors: Hsu, Shin-yi
• Primary Examiner(s): Couso, Jose L.
• Application Number:
  US08/709,918
• Time in Patent Office: 1,534 Days
• Field of Search: 382/103, 382/173, 382/153, 382/155, 382/157, 382/181, 382/190, 382/199, 382/203, 382/240, 382/284, 382/285, 364/274.6, 395/61, 348/116-120, 348/122, 348/123
• US Class Current: 382/294
• CPC Class Codes: G06T 2207/10028 Range image; Depth image; 3D point clouds
• CPC Class Codes: G06T 2207/10036 Multispectral image; Hyperspectral image
• CPC Class Codes: G06T 2207/20016 Hierarchical, coarse-to-fine, multiscale or multiresolution image processing; Pyramid transform
• CPC Class Codes: G06T 2207/20084 Artificial neural networks [ANN]
• CPC Class Codes: G06T 2207/30181 Earth observation
• CPC Class Codes: G06T 2207/30212 Military
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/12 Edge-based segmentation
• CPC Class Codes: G06T 7/143 involving probabilistic approaches, e.g. Markov random field [MRF] modelling
• CPC Class Codes: G06T 7/174 involving the use of two or more images
• CPC Class Codes: G06V 10/255 Detecting or recognising potential candidate objects based on visual cues, e.g. shapes
• CPC Class Codes: G06V 10/754 involving a deformation of the sample pattern or of the reference pattern; Elastic matching
• CPC Class Codes: G06V 20/13 Satellite images
• CPC Class Codes: G06V 20/64 Three-dimensional objects

Abstract

The present invention features the use of the fundamental concept of color perception and multi-level resolution to perform scene segmentation and object/feature extraction in the context of self-determining and self-calibration modes. The technique uses only a single image, instead of multiple images as the input to generate segmented images. Moreover, a flexible and arbitrary scheme is incorporated, rather than a fixed scheme of segmentation analysis. The process allows users to perform digital analysis using any appropriate means for object extraction after an image is segmented. First, an image is retrieved. The image is then transformed into at least two distinct bands. Each transformed image is then projected into a color domain or a multi-level resolution setting. A segmented image is then created from all of the transformed images. The segmented image is analyzed to identify objects. Object identification is achieved by matching a segmented region against an image library. A featureless library contains full shape, partial shape and real-world images in a dual library system. The depth contours and height-above-ground structural components constitute a dual library. Also provided is a mathematical model called a Parzen window-based statistical/neural network classifier, which forms an integral part of this featureless dual library object identification system. All images are considered three-dimensional. Laser radar based 3-D images represent a special case.

Claims

1. A system for segmenting an image and extracting objects and features therefrom, comprising:

a) image preprocessing means for receiving and analyzing information representative of maps, images, data or a combination thereof, said image preprocessing means comprising;

i) means for retrieving an original image, each pixel of which has a value represented by a predetermined number of bits, n;

ii) means for transforming said original image into at least two distinct bands, each of said pixels in each of the band-images comprising no more than n bits;

iii) means for protecting each of said transformed, band-images, into a composite domain; and

iv) means for creating a composite image from all of said transformed, band-images;

b) main processing means operatively connected to said image preprocessing means, for analyzing preprocessed information in accordance with interrogation rules;

c) a knowledge base, operatively connected to said image processing means, for storing rules and models and for matching analyzed information from said main processing means with said stored models; and

d) means for outputting, operatively connected to said main processing means and to said image preprocessing means, for displaying images and for providing object files to said image preprocessing means.

2. The system for segmenting and extracting in accordance with claim 1, further comprising:

e) storage means operatively connected to said image preprocessing means and to said main processing means.

3. The system for segmenting and extracting in accordance with claim 1, wherein said knowledge base comprises a dual library for storing information representative of three-dimensional objects.

4. The system for segmenting and extracting in accordance with claim 3, wherein said dual library comprises full and partial images of at least one of said models and up-dated real world images that constitute a mixed library.

5. The system for segmenting and extracting in accordance with claim 4, wherein said image preprocessing means comprises:

i) level one preprocessing means for vector-to-vector raster converting,

ii) level two preprocessing means for filtering and transforming, and

iii) level three preprocessing means for integrating raster- and vector-based segmentation analysis.

6. The system for segmenting and extracting in accordance with claim 5, further comprising:

e) storage means operatively connected to said image preprocessing means and to said main processing means.

7. The system for segmenting and extracting in accordance with claim 1, wherein said image preprocessing means further comprises:

v) means for digitizing said composite image, if necessary; and

vi) means for analyzing regions in said segmented images to identify objects.

8. The system for segmenting and extracting in accordance with claim 1, wherein said image preprocessing means further comprises:

vii) means for coordinating said composite image with independently-generated information to identify features and objects.

9. The system for segmenting and extracting in accordance with claim 1, wherein said means for transforming comprises means for compressing said original image, each of said bands using a different compression factor or technique.

10. The system for segmenting and extracting in accordance with claim 9, wherein said means for compressing comprises means for extracting the square root of the pixel values.

11. The system for segmenting and extracting in accordance with claim 9, wherein said means for compressing comprises means for extracting the log of the pixel values.

12. The system for segmenting and extracting in accordance with claim 9, wherein said means for compressing comprises means for extracting the double log of the pixel values.

13. The system for segmenting and extracting in accordance with claim 9, wherein said means for compressing comprises means for filtering said pixel values thereof.

14. The system for segmenting and extracting in accordance with claim 1, wherein said means for transforming comprises means for reducing bits and remapping without compression.

15. The system for segmenting and extracting in accordance with claim 7, further comprising:

vii) means for coordinating said composite image with independently-generated information to label each segmented image with a set of interrogation rules.

16. The system for segmenting and extracting in accordance with claim 7, further comprising:

vii) means for coordinating said composite image with independently-generated information to match each segmented image against a predetermined library.