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Rapid image splicing method based on point and line features

An image mosaic and line feature technology, which is applied in image enhancement, image data processing, graphics and image conversion, etc., can solve the problems of small number of effective points to be matched, insufficient number of feature points, and inability to fully reflect image details, etc.

Active Publication Date: 2014-03-26
JIANGSU R & D CENTER FOR INTERNET OF THINGS
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Problems solved by technology

[0007] The purpose of the present invention is to solve the problems that the extracted features cannot fully reflect the image details, the number of feature points is insufficient, and the number of effective points to be matched is small in the process of image feature matching, and a fast image stitching method based on dual features of points and lines is proposed, which can Enhance image details and improve image stitching quality

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  • Rapid image splicing method based on point and line features
  • Rapid image splicing method based on point and line features
  • Rapid image splicing method based on point and line features

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Embodiment Construction

[0050] The present invention will be further described below in conjunction with the drawings and embodiments.

[0051] The matching objects of the present invention are two photos of the same scene, the two images were taken at different times and different angles, and the exposures of the two images are different, only part of the content is the same, and the size of the images is 254*509. Choose one of them One is the reference image, and the other is the image to be registered. The simulation verification of the method is based on the processing on the matlab7.8.0 simulation platform. Such as figure 1 As shown, the present invention generally includes the following steps:

[0052] 1. Extract line features on the reference image and the image to be registered, and the Canny edge extraction method is preferred in the embodiment.

[0053] 2. Use the extracted line features to superimpose the reference image and the image to be registered.

[0054] 3. Extract point features from the...

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Abstract

The invention provides a rapid image splicing method based on feature matching. The method includes the steps: respectively extracting line features and point features of images by the aid of a Canny edge detection algorithm and a Harris corner point detection algorithm and combining the line features and the point features to obtain the best feature points; roughly matching the feature points by the aid of similarity metric NCC (normalized cross correlation), removing mismatched points by the aid of an RANSAC (random sample consensus) algorithm to improve image matching accuracy, and calculating transformation model parameters by an LSM (least square method); finally, fusing the spliced images by a weighted average method and eliminating splicing gaps. The points to the matched are determined according to the point and line image features, image details can be enhanced, image matching errors caused by underexposure, overexposure, camera shake and the like are avoided, and image splicing quality is improved to a certain degree.

Description

Technical field [0001] The invention belongs to the field of image processing and pattern recognition, and specifically relates to a fast image splicing method based on the dual features of points and lines. Background technique [0002] The image feature is the most basic attribute to distinguish the internal elements of the image, and the image features participating in the matching constitute the feature space. Features are divided into artificial features and natural features. The former are features specified for image analysis and processing, such as image histograms, moment invariants, image frequency spectrum, high-level structure descriptions, etc.; the latter are inherent to the image, such as image gray Degree, color, outline, corner point, line intersection, etc. The selection of image features is very important, it is related to the complexity and computational complexity of the search matching algorithm. The selected feature must meet three requirements: 1. The se...

Claims

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Application Information

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IPC IPC(8): G06T3/40G06T5/00
Inventor 方圆圆张雷
Owner JIANGSU R & D CENTER FOR INTERNET OF THINGS
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