Optimized depth extraction and passive ranging method based on monocular vision

Abstract

The invention discloses an optimized depth extraction and passive ranging method based on monocular vision, which is characterized in that it includes the following steps: Step 1: Calibrate the camera of a mobile phone, and obtain internal camera parameters and image resolution; Step 2: Step 3 of establishing a depth extraction model: Obtain the pixel values ​​u' and v' of the target point through image acquisition of the target object to be measured; Step 4: Use the internal parameters of the camera and the pixel value of the target point obtained in the above steps and combine the camera depth extraction model, Calculate the distance L between any point on the image of the target object to be measured and the camera of the mobile phone. The optimized depth extraction and passive ranging method based on monocular vision of the present invention can be applied to parameters such as field of view, focal length, and image resolution. Different cameras improve the ranging accuracy and provide support for target measurement in machine vision and 3D reconstruction of real scenes.

Description

technical field [0001] The invention relates to the field of ground close-range photogrammetry, in particular to a passive ranging method for a pinhole camera under a monocular vision system. Background technique [0002] Image-based target ranging and positioning, mainly divided into two methods: active ranging and passive ranging [1] . Active ranging is to install a laser ranging device on a machine (such as a camera) for ranging [2-4] . Passive ranging is to calculate the depth information of the target object in the two-dimensional digital image through machine vision, and then calculate the target object distance according to the image pixel information and camera imaging principle [5-6] . Machine vision distance measurement is mainly divided into two types: monocular vision distance measurement and binocular vision distance measurement [7-9] . In the ranging process, the key step is to obtain the depth information of the target object. The early methods of obtain...

AI Technical Summary

Problems solved by technology

Due to the differences in the internal parameters of different camera devices, for different types of camera devices, this method needs to re-acquire target image information and establish a camera depth information extraction model, and different vehicle-mounted cameras have different camera pitch angles due to lens manufacturing and assembly. There will be differences, so the method in [21] is less general

[0006] In addition, the method of literature [21] uses a vertical target to study the relationship between the imaging angle of the vertical plane image point and the pixel value of the vertical coordinate, and applies this to the measurement of the object distance on the horizontal plane, which makes the ranging accuracy relatively low , because the camera’s horizontal and vertical distortion laws are not exactly the same

The invention application with the application number 201710849961.3 discloses an improved camera calibration model and distortion correction model suitable for smart mobile cameras (hereinafter referred to as: improved calibration model with nonlinear distortion items), which can help correct Calibrate the image of the board to obtain higher-precision camera internal and external parameters. The disadvantage is that this method has not been extended to the nonlinear distortion correction of the image to be tested and the measurement of the target object.

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