Panoramic Image Stitching Method Based on Bag-of-Words Model

A bag-of-words model and panoramic image technology, applied in image analysis, graphic image conversion, image data processing, etc., can solve problems such as inapplicability of real-time performance, and achieve the effect of shortening algorithm time, reducing algorithm time, and ensuring stitching effect.

Active Publication Date: 2020-03-20
TIANJIN UNIV
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

However, most of the image stitching methods at this stage are based on frame-to-frame comparison methods. This method can receive good results when the number of images is small. Not applicable when higher

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  • Panoramic Image Stitching Method Based on Bag-of-Words Model
  • Panoramic Image Stitching Method Based on Bag-of-Words Model
  • Panoramic Image Stitching Method Based on Bag-of-Words Model

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Embodiment Construction

[0028] The present invention proposes a multi-thread panoramic image mosaic technology based on the bag-of-words model, which is described in detail in conjunction with examples and accompanying drawings as follows:

[0029] The overall framework of the algorithm of the present invention is as figure 1 As shown, the system is divided into four parts and these four parts can run in parallel. This parallel design can reduce the coupling between each part, thereby reducing the running time of the algorithm. These four parts are connected by a structure called mosaic structure graph, which is used to estimate the topological structure of the mosaic environment, and at the same time, it is used to coordinate the relationship between various parts to ensure real-time performance.

[0030] The mosaic structure diagram part is an important part of the method of the present invention, wherein the topology diagram represents the topology structure of the mosaic environment and unifies t...

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Abstract

The invention relates to a bag-of-word-based panoramic picture splicing method. The method comprises: a trained ORB word bag tree is prepared; ORB feature extraction is carried out on an image i in a to-be-spliced image data set, a k is set to be a last key frame inserted into a spliced structural graph, feature searching is carried out on two images by forward indexing and correspondence between the features is established, so that the correspondence of features of the two images is obtained; a homographic matrix between the two images is obtained; with a random sampling maximum likelihood estimation algorithm, a secondary projection error is minimized and an exterior point is eliminated, so that an interior point set of a corresponding image pair is obtained; on the basis of a boundary matrix, an overlap percentage of the images is calculated; overlapping between the corresponding image pairs is calculated, and connection with a previous key frame needs to be established by the homographic matrix when the image i is added into the spliced structural graph as a key frame; a loop is detected; a loop is formed; the homographic matrix is optimized; and fusion of image splicing structural graphs is carried out.

Description

technical field [0001] The invention belongs to the fields of computer vision and digital image processing. Background technique [0002] Image mosaic technology is an important branch in the field of computer vision and digital image processing. It is a technology that seamlessly stitches more than two partially overlapping images to obtain higher resolution or wide viewing angle images. The two most critical links in image stitching are image registration and image fusion. For image fusion technology, the current method has little difference in time consumption and fusion effect, and it has become mature. But for image registration, because its registration time and effect directly affect the speed and success rate of image stitching, image registration has always been a hot spot in the research of image stitching. Common image registration methods are based on SIFT or SURF features to describe images. The advantages of these feature descriptors are rotation invariance, ...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06T3/40G06T3/00G06T7/33
CPCG06T3/0068G06T3/4038G06T7/337
Inventor 张国山张玉龙黄伟杰
Owner TIANJIN UNIV
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