Method and apparatus for image retrieval

• US 20030198387A1
• Filed: 04/22/2002
• Published: 10/23/2003
• Est. Priority Date: 04/22/2002
• Status: Abandoned Application

• Current Assignee: Bengal Engineering College, Intel Corporation
• Original Assignee: Intel Corporation
• Inventors: Chanda, Bhabatosh, Das, Amit K., Saha, Sanjoy K., Acharya, Tinku
• Application Number:
  US10/128,601
• Publication Number:
  US 20030198387A1
• Time in Patent Office: Days
• US Class Current: 382/199
• CPC Class Codes: G06T 2207/20032 Median filtering
• CPC Class Codes: G06T 2207/20192 Edge enhancement; Edge preservation
• CPC Class Codes: G06T 5/002 Denoising; Smoothing noise processing or correction adapted to be used in an image pickup device containing and electronic image sensor H04N23/81, H04N25/60 - H04N25/67
• CPC Class Codes: G06T 5/20 using local operators
• CPC Class Codes: G06T 5/70 Denoising; Smoothing
• CPC Class Codes: G06T 7/11 Region-based segmentation
• CPC Class Codes: G06T 7/136 involving thresholding
• CPC Class Codes: G06T 7/194 involving foreground-background segmentation
• CPC Class Codes: G06V 10/42 Global feature extraction by analysis of the whole pattern, e.g. using frequency domain transformations or autocorrelation
• CPC Class Codes: G06V 10/46 Descriptors for shape, contour or point-related descriptors, e.g. scale invariant feature transform [SIFT] or bags of words [BoW]; Salient regional features colour feature extraction G06V10/56
• CPC Class Codes: G06V 10/507 Summing image-intensity values; Histogram projection analysis

Abstract

Embodiments of a method and/or apparatus for retrieving images are disclosed.

Claims

1. A method of processing an initial image comprising:

applying noise reduction;

producing another image to detect discontinuities in gray levels; and

removing less significant discontinuities.

2. The method of claim 1, wherein applying noise reduction includes applying a median filter to the initial image to produce a filtered image.

3. The method of claim 2, wherein the median filter is applied across the image in 5 by 5 neighborhoods.

4. The method of claim 2, wherein producing another image to detect discontinuities in gray levels includes producing a gradient image from the filtered image.

5. The method of claim 4, wherein removing less significant discontinuities includes thresholding the gradient image.

6. The method of claim 5, and further comprising, identifying a contour of an object of the initial image by scanning the thresholded gradient image.

7. The method of claim 6, and further comprising, computing at least one scale invariant feature from the contour of the object identified.

8. The method of claim 7, wherein the at least one substantially scale invariant feature of the object is compared with a corresponding substantially scale invariant feature of a plurality of images.

9. The method of claim 7, wherein the at least one substantially scale invariant feature of the contour of the object includes at least one of the following:

moment, directional area gradient, circularity and aspect ration.

10. The method of claim 6, and further comprising, computing more than one scale invariant feature from the contour of the object identified.

11. The method of claim 10, wherein the more than one substantially scale invariant feature of the object is compared with more than one corresponding substantially scale invariant features of a plurality of images.

12. The method of claim 11, wherein the more than one substantially scale invariant feature of the contour of the object includes at least more than one of the following:

moment, directional area gradient, circularity and aspect ration.

13. An article comprising:

a storage medium having stored thereon instructions that, when executed, result in the following;

applying noise reduction;

producing another image to detect discontinuities in gray levels; and

removing less significant discontinuities.

14. The article of claim 13, wherein, said instructions, when executed, result in applying noise reduction that further includes applying a median filter to the initial image to produce a filtered image.

15. The article of claim 13, wherein, said instructions, when executed, result in producing another image to detect discontinuities in gray levels that further includes producing a gradient image from the filtered image.

16. The article of claim 15, wherein, said instructions, when executed, result in removing less significant discontinuities that further includes thresholding the gradient image.

17. The article of claim 16, wherein, said instructions, when executed, result in further identifying a contour of an object of the initial image by scanning the thresholded gradient image.

18. The article of claim 17, wherein, said instructions, when executed, result in computing at least one scale invariant feature from the contour of the object identified.

19. A system comprising:

a computing platform, said computing platform having the capability to process an initial image by;

detecting discontinuities in gray levels; and

removing less significant discontinuities.

20. The system of claim 19, wherein the computing platform comprises a computer.

21. The system of claim 19, wherein said computing platform further includes the capability to reduce noise in the initial image.

22. The system of claim 21, wherein said computing platform has the capability to detect discontinuities in gray levels in the initial image by producing a gradient image.

23. The system of claim 22, wherein said computing platform has the capability to remove less significant discontinuities by thresholding.