Method for measuring distance based on single image

Abstract

The invention relates to a method for measuring the distance based on a single image in the field of application software of photographic equipment. The method comprises the following steps: using a single defocus image to extract a fuzzy edge in the image and measure an approximate value of the width of the fuzzy edge and the gray scale difference of two sides of the fuzzy edge; training a BP neural network by using the corresponding relation of distance information of the approximate value and the gray scale difference, the focal distance and the aperture diameter; and calculating the distance information by using the well-trained BP neural network. The method can be applied to equipment with variable focal distance and aperture, the measurement of the distance only needs one defocus image, the calculation amount is not large, and the speed is quicker.

Description

technical field [0001] The present invention relates to a distance measuring method in the technical field of photography equipment, in particular to a distance measuring method based on a single image. Background technique [0002] The distance information of the object in the image is the distance from the captured object to the lens. It is very important to measure the distance information in the fields related to machine vision such as automatic focusing and three-dimensional reconstruction. Distance measurement methods can generally be divided into active and passive methods. Active methods include infrared ranging method, structured light method, moiré fringe method, etc. Passive methods include mobile ranging, zooming, and defocus ranging. The advantages of the active method are high precision and strong anti-interference ability, but it uses the sending and receiving of light waves for distance measurement, which requires additional equipment and high cost. The ac...

AI Technical Summary

Problems solved by technology

The disadvantages of this method are: 1. It is only suitable for lenses with a fixed focal length, and cannot be applied to camera equipment with a variable focal length.

2. Each image area needs to be Fourier transformed and multiplied by the inverse function of multiple defocus functions that have been converted to the frequency domain, and then the result with the highest proportion of high-frequency components is selected, which requires a large amount of calculation.

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