IMAGE MATCHING METHOD AND APPARATUS

• US 20140226906A1
• Filed: 02/14/2013
• Published: 08/14/2014
• Est. Priority Date: 02/13/2013
• Status: Abandoned Application

• Current Assignee: Samsung Electronics Co. Ltd.
• Original Assignee: Samsung Electronics Co. Ltd.
• Inventors: KANG, Woo-Sung
• Application Number:
  US13/767,340
• Publication Number:
  US 20140226906A1
• Time in Patent Office: Days
• US Class Current: 382/197
• CPC Class Codes: G06V 10/462 Salient features, e.g. scale invariant feature transforms [SIFT]
• CPC Class Codes: G06V 10/757 Matching configurations of points or features

Abstract

Methods and apparatus are provided for image matching. A first image is received via an external input. One or more feature points are extracted from the first image. One or more descriptors are generated for the first image based on the one or more feature points. The first image is matched with a second image by comparing the one or more descriptors for the first image with one or more descriptors for the second image.

Claims

1. An image matching apparatus comprising:

an image input unit for receiving a first image;

a feature extractor for extracting one or more feature points from the first image;

a descriptor generator for generating one or more descriptors for the first image based on the one or more feature points; and

an image matcher for matching the first image with a second image by comparing the one or more descriptors for the first image with one or more descriptors for the second image.

2. The image matching apparatus of claim 1, wherein the descriptor generator normalizes an image patch having the one or more feature points by rotating the one or more feature points for the first image.

3. The image matching apparatus of claim 1, wherein the descriptor generator obtains feature point descriptors in a binary string form using the one or more feature points.

4. The image matching apparatus of claim 3, wherein the image matcher performs an XOR operation between the feature point descriptors in the binary string form using Hamming distance, and obtains feature vectors for respective image patches included in the first image by counting a number of “

1'"'"'s”

included in a value resulting from the XOR operation.

5. The image matching apparatus of claim 4, wherein the image matcher generates a hash table using the feature vectors, and searches data from the hash table for matching the first image with the second image.

6. An image matching method comprising the steps of:

receiving a first image via an external input;

extracting one or more feature points from the first image;

generating one or more descriptors for the first image based on the one or more feature points; and

matching the first image with a second image by comparing the one or more descriptors for the first image with one or more descriptors for the second image.

7. The image matching method of claim 6, prior to generating the one or more descriptors for the first image, further comprising:

normalizing one or more image patches included in the first image.

8. The image matching method of claim 7, wherein normalizing the one or more image patches comprises rotating the one or more feature points within the one or more image patches included in the first image, and

wherein generating the one or more descriptors for the first image comprises obtaining feature point descriptors in a binary string form using the one or more rotated feature points, performing an XOR operation between the feature point descriptors in the binary string form using Hamming distance, and obtaining feature vectors for respective image patches included in the first image by counting a number of “

1'"'"'s”

included in a value resulting from the XOR operation.

9. The image matching method of claim 7, wherein generating the one or more descriptors for the first image comprises obtaining feature point descriptors in a binary string form using the one or more feature points, performing an XOR operation between the feature point descriptors in the binary string form using Hamming distance, and obtaining feature vectors for respective image patches included in the first image by counting a number of “

1'"'"'s”

included in a value resulting from the XOR operation.

10. The image matching method of claim 9, further comprising generating a hash table by using the feature vectors.

11. The image matching method of claim 10, prior to matching the first image and the second image, further comprising:

searching data from the hash table for matching the first image with the second image.