Detection method of checkboard grid image angular point sub pixel

A detection method and checkerboard technology, which are applied in image analysis, image data processing, instruments, etc., can solve the problems of difficulty in obtaining detection accuracy, large exposure, and low detection accuracy, and achieve stable measurement results, simple and good detection process. The effect of detection accuracy

Inactive Publication Date: 2014-07-16
UNIV OF SHANGHAI FOR SCI & TECH
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Problems solved by technology

This type of algorithm avoids the above-mentioned defects in the method of corner detection based on edge detection, and has good comprehensive performance, but there are still some limitations. For example, in the method disclosed in prior art document 3, when in a complex Under background conditions, it is difficult to obtain better detection accuracy. In the methods disclosed in prior art document 4, prior art document 5, and pri

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  • Detection method of checkboard grid image angular point sub pixel
  • Detection method of checkboard grid image angular point sub pixel
  • Detection method of checkboard grid image angular point sub pixel

Examples

Experimental program
Comparison scheme
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Embodiment 1

[0061] figure 1 It is a flow chart of the checkerboard image corner sub-pixel detection method involved in the present invention.

[0062] The detection method of the checkerboard image corner sub-pixel provided by the first embodiment is as follows: figure 1 shown, including the following three steps:

[0063] figure 2 is the acquired image of the checkerboard calibration template.

[0064] image 3 is the binarized image of the checkerboard calibration template.

[0065] Step 1 (S1): Use the NI1778 camera and the Computar M1620-MPV lens to shoot the checkerboard calibration template, and obtain the following figure 2 As shown in the image of the checkerboard calibration template, in the template image of the first embodiment, the side length of each checkerboard is 5 mm, and the accuracy is 0.0015 mm.

[0066] Using the maximum between-class variance method to binarize the template image, we get the following image 3 As shown in the binarized image, the binarized i...

Embodiment 2

[0103] Figure 10 It is an explanatory diagram of corner point results after detection is completed by using the method provided by the present invention in Example 2.

[0104] Figure 11 It is an explanatory diagram of corner point results after detection is completed using the detection method provided by prior art document 4 in Example 2.

[0105] Figure 12 It is an explanatory diagram of corner point results after detection is completed using the detection method provided by prior art document 7 in Example 2.

[0106] With reference to the detection method provided in Embodiment 1, the template image of the checkerboard calibration template under a certain complex background is detected, and the following is obtained after detection: Figure 10 The image shown, where Figure 10 -b for Figure 10 -A partial enlarged view, as can be seen from the figure, the detection method provided by this example can detect all corner points in the image without missed detection or ...

Embodiment 3

[0110] Figure 13 is the reprojection result map of the detected corners.

[0111] Figure 14 is the reprojection error map of the detected corners.

[0112] Collect five checkerboard images, perform corner detection with reference to the method provided by the present invention, and use Zhang Zhengyou’s camera calibration principle to perform camera calibration. One of the corner reprojection results obtained after calibration is as follows Figure 13 As shown, the corner projection error is as Figure 14 As shown, the average reprojection error of the corner points is (0.247, 0.205) pixels.

[0113] In addition, in addition to binarizing the template image using the maximum inter-class variance method used in the detection method of the checkerboard image corner sub-pixels involved in the present invention, other methods that can better distinguish the black and white areas of the checkerboard image can also be used. The binarization method performs binarization, such as...

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Abstract

The invention provides a detection method of a checkboard grid image angular point sub pixel. The detection method of the checkboard grid image angular point sub pixel comprises the steps that 1, a checkboard grid calibration template is filmed trough a camera, a template image of the checkboard grid calibration template is obtained, and binaryzation is conducted on the template image to obtain a binaryzation image; 2, traversal is conducted on the binaryzation image through a circular template, and screening is conducted on all the tested pixel points of the binaryzation image to screen out candidate angular points; 3, according to the character of the candidate angular points that the candidate angular points are symmetrically arranged near a true angular point which is determined by an angular point set, the abscissa average value and the ordinate average value of the pixel positions of the candidate angular points are calculated, and the abscissa average value and the ordinate average value serve as the sub pixel coordinates of the true angular point. According to the detection method of the checkboard grid image angular point sub pixel, only simple arithmetic is needed, and operations of differential, interpolation, surface fitting and the like are not needed, so that the detection process is simple and easy to realize, sub pixel level precision can be directly obtained, and good detection precision and real-time are obtained.

Description

technical field [0001] The invention belongs to a detection method in the technical field of camera calibration, in particular to a detection method of a checkerboard image corner sub-pixel. Background technique [0002] The checkerboard calibration template is widely used in camera calibration technology because of its simple features, obvious contrast, and easy identification. The accuracy of checkerboard image corner detection directly determines the calibration accuracy of the camera, which in turn affects the accuracy of subsequent tasks such as visual measurement. Therefore, improving the accuracy of corner detection in checkerboard images is an important research topic in the field of visual measurement. Currently, checkerboard image corner detection methods can be divided into corner detection methods based on edge detection and corner detection methods based on grayscale changes. [0003] Prior Art Document 1 and Prior Art Document 2 provide two different methods ...

Claims

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Application Information

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IPC IPC(8): G06T7/00
Inventor 朱坚民李记岗战汉张统超李孝茹齐北川
Owner UNIV OF SHANGHAI FOR SCI & TECH
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