Image matching method based on SIFT features and distortion-preserving mapping

A matching method and image technology, applied in character and pattern recognition, instruments, computing, etc., can solve problems such as wrong matching, matching results that are not optimal matching, and inability to meet application requirements, so as to improve accuracy and reduce wrong matching. Effect

Active Publication Date: 2019-06-21
CHAOHU UNIV
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Problems solved by technology

[0006] However, the feature points detected by the image matching method based on classical descriptors or geometric topological relations are only identifiable feature points in an ideal state. When affected by conditions such as illumination and perspective changes, it is easy to appear a The problem that the feature points in the image are not

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  • Image matching method based on SIFT features and distortion-preserving mapping
  • Image matching method based on SIFT features and distortion-preserving mapping
  • Image matching method based on SIFT features and distortion-preserving mapping

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Embodiment 1

[0054] Such as figure 1 As shown, the present invention adopts a kind of image matching method based on SIFT feature and distortion-preserving mapping, comprises following steps S1 to S4:

[0055] S1. Use the SIFT algorithm to obtain corresponding feature points between the source image and the target image, and use the corresponding feature points as a candidate matching set;

[0056] S2. Establish a triangular mesh mapping between the source image and the target image according to the corresponding feature points in the candidate matching set;

[0057] S3. Adding distortion-preserving constraints in the triangular mesh mapping;

[0058]S4. Under the distortion-preserving constraint condition, optimize the objective function formed by the corresponding feature points in the candidate matching set to realize the matching between the source image and the target image.

[0059] Specifically, the SIFT algorithm is used to obtain the corresponding feature points between the sour...

Embodiment 2

[0144] Such as image 3 As shown, the present invention adopts a kind of image matching system based on SIFT feature and distortion-preserving mapping, including feature point extraction module 10, mapping module 20, adding module 30 and matching module 40;

[0145] The feature point extraction module 10 is used to use the SIFT algorithm to obtain corresponding feature points between the source image and the target image, and use the corresponding feature points as a candidate matching set;

[0146] The mapping module 20 is used to set up a triangular mesh mapping between the source image and the target image according to the corresponding feature points in the candidate matching set;

[0147] Adding module 30 is used for adding in triangular grid mapping and guarantees the distortion constraint condition;

[0148] The matching module 40 is used to optimize the objective function formed by the corresponding feature points in the candidate matching set under the distortion-pre...

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Abstract

The invention discloses an image matching method based on SIFT (scale invariant feature transform) features and distortion-preserving mapping, which belongs to the field of computer image processing and comprises the following steps of: acquiring corresponding feature points between a source image and a target image by using an SIFT algorithm, and taking the corresponding feature points as a candidate matching set; establishing triangular mesh mapping between a source image and a target image according to corresponding feature points in the candidate matching set; adding a distortion-maintaining constraint condition in the triangular mesh mapping; and optimizing an objective function formed by corresponding feature points in the candidate matching set under a distortion-maintaining constraint condition to realize matching between the source image and the target image. According to the invention, the accuracy of image matching is improved.

Description

technical field [0001] The invention relates to the field of computer image processing, in particular to an image matching method based on SIFT features and distortion-preserving mapping. Background technique [0002] Image matching is one of the classic problems in computer vision, and its goal is to find the best feature point correspondence between images. Many existing algorithms are dedicated to solving the problem of image matching, such as image matching methods based on classical descriptors and geometric topological relations, among which methods based on classical descriptors are widely used, including scale-invariant feature transformation algorithms (Scale InvariantFeature Transform, SIFT), Fast Robust Feature Algorithm (Speeded Up Robust Features, SURF), SIFT-based methods and SURF-based methods. [0003] SIFT provides multi-scale matching between images, so that the features remain unchanged when the image is translated, scaled, and rotated. This method is mor...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06K9/46
Inventor 张勇吴其林张正金徐秋月王小超
Owner CHAOHU UNIV
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