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Image splicing method based on improved ORB feature algorithm

An image mosaic and algorithm technology, applied in the field of computer vision, can solve the problems of low accuracy of matching points, ORB algorithm does not have scale invariance, etc.

Pending Publication Date: 2020-10-16
CHANGAN UNIV
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AI Technical Summary

Problems solved by technology

[0006] The ORB (Oriented FAST and Rotated Brief) algorithm is a fast feature point extraction and description algorithm. The ORB algorithm is divided into two parts, namely feature point extraction and feature point description. It has the advantage of fast calculation speed, but the traditional ORB The algorithm still has the problems of not having scale invariance and low accuracy of matching point pairs

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  • Image splicing method based on improved ORB feature algorithm
  • Image splicing method based on improved ORB feature algorithm
  • Image splicing method based on improved ORB feature algorithm

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Embodiment Construction

[0065] In order to describe technical content of the present invention, operation process, realized purpose and effect in detail, provide following embodiment description.

[0066] refer to figure 1 , an image mosaic method based on the improved ORB feature algorithm, comprising the following steps:

[0067] Step 1, preprocessing the image to be stitched, then constructing the Hessian matrix, using the local extremum of the Hessian matrix to determine the feature points of each image to be stitched;

[0068] First, the preprocessing of the images to be stitched is: performing spatial geometric transformation on the images to be stitched, that is, operations including translation, rotation, and scaling for alignment.

[0069] Then, build a scale pyramid on the image to obtain scale-invariant feature points, that is, the required feature points are feature points that appear in each scale space, so that the blurring degree of different layers of images is different, while using...

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Abstract

The invention discloses an image splicing method based on an improved ORB feature algorithm. The method comprises the following steps: constructing a Hessian matrix, and determining feature points ofeach to-be-spliced image; extracting a feature descriptor of each image to be spliced by using a BRIEF binary feature descriptor; performing rough matching by using a Hamming distance, and distinguishing correct matching point pairs from wrong matching point pairs by using a grid motion feature algorithm; removing error matching feature point pairs by using an improved random sampling consistencyalgorithm; searching an optimal suture line; dividing an overlapping region; and performing segmented fusion to complete image splicing. Through the multi-scale space theory, the Hessian matrix and the Gaussian pyramid are used for improving the registration method, the purpose of scale invariance is achieved, and meanwhile the matching precision of the matching point pairs is improved.

Description

technical field [0001] The invention belongs to the technical field of computer vision, in particular to an image splicing method based on an improved ORB feature algorithm. Background technique [0002] Images play an important role in the information dissemination of human social activities. Vision is one of the important channels for information acquisition. Everything in nature is displayed in the form of "images" in the human brain through the visual system. With the continuous improvement of computer vision-related technologies, it is difficult for ordinary cameras to obtain high-resolution and large-field images due to the limited viewing angle. Although panoramic cameras can meet people's needs, their prices are too high and the market demand changes. Vision Technology conducts research on image stitching. [0003] Image stitching is a widely used image processing technology. The main process usually includes determining the overlapping parts of the image, performin...

Claims

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Application Information

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IPC IPC(8): G06T3/40G06T5/00G06T5/50G06T7/90G06K9/62
CPCG06T3/4038G06T5/50G06T7/90G06T2207/20221G06T2200/32G06V10/757G06T5/70
Inventor 任卫军王茹黄金文张力波吴学致
Owner CHANGAN UNIV
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