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Fisheye image correction method based on changed long axis ellipse fitting

A fisheye image and ellipse fitting technology, applied in image enhancement, image data processing, instruments, etc., can solve the problems of insufficient real-time performance, insufficient, excessive correction and correction, etc., and achieve the effect of simple algorithm, easy transplantation, and strong real-time performance.

Active Publication Date: 2014-08-20
NORTHEASTERN UNIV
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Problems solved by technology

However, optimization algorithms such as neural networks have the problems of complex algorithms and insufficient real-time performance, making it difficult to transplant embedded devices and mobile devices
Moreover, since the optimization algorithm is a black-box model, the selection of image samples has a great influence on the corrected mapping relationship after training. If the selected samples are not typical, the corrected image obtained by the optimization algorithm will lead to over-correction or under-correction. Happening

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  • Fisheye image correction method based on changed long axis ellipse fitting
  • Fisheye image correction method based on changed long axis ellipse fitting
  • Fisheye image correction method based on changed long axis ellipse fitting

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Embodiment Construction

[0024] The specific embodiments of the present invention will be described in detail below in conjunction with the accompanying drawings.

[0025] The software environment of this embodiment is the WINDOWS7 system, the simulation environment is MATLAB R2014a, and the processor is the second generation Core i5-2410.

[0026] The fisheye image correction method based on variable length ellipse fitting in this embodiment, such as figure 1 shown, including the following steps:

[0027] Step 1. Convert the color fisheye image into a grayscale fisheye image.

[0028] Due to the large amount of color image information and the inconspicuous grayscale features, the processing burden of the algorithm is increased. In this embodiment, the grayscale conversion function of the MATLAB R2014a system is used to convert the color fisheye image into a grayscale fisheye image. The grayscale image has 640 pixels. ×480.

[0029] Step 2. Use the global grayscale average value of the grayscale fi...

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Abstract

The invention provides a fisheye image correction method based on changed long axis ellipse fitting. A changed long axis ellipse fitting correction model is built, the model is based on a longitude and latitude mapping correction algorithm, a longitude long axis parameter and a latitude long axis parameter are adjusted at the same time, and a finial changed long axis ellipse fitting correction model is obtained; according to coordinates of pixels of a fisheye image, through the changed long axis ellipse fitting correction model, corresponding pixel coordinates of the fisheye image under pixel coordinates are obtained, and a fisheye correction image is obtained. The mapping conditions of the pixels are recorded in the full correction process through a table mapping method, and the final correction image is obtained. The fisheye image correction method based on changed long axis ellipse fitting has the advantages of being simple in algorithm and high in real-time performance, and enables the transplanting of an embedded type device and a mobile device to be easy.

Description

technical field [0001] The invention relates to the technical field of machine vision, in particular to a fisheye image correction method based on variable length ellipse fitting. Background technique [0002] The fisheye lens is a kind of super wide-angle lens. In order to achieve the maximum viewing angle of the lens, the diameter of the front lens of the lens is very short and protrudes toward the front of the lens in a parabolic shape. The fisheye lens has a short focal length and a large viewing angle, and there is a geometric optical error between its imaging point and the ideal imaging point, also known as distortion. In the actual optical imaging system of camera and lens combination, the causes of distortion are mainly divided into two categories: radial distortion and eccentric distortion. Radial distortion refers to the change of radial curvature that causes the actual imaging point to deviate radially from the ideal imaging point. The farther the deformation is ...

Claims

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Application Information

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IPC IPC(8): G06T5/00G06K9/38
Inventor 朱德龙张云洲钟惟林廖峭
Owner NORTHEASTERN UNIV
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