Monocular camera object identification and positioning method based on vector illumination influence removing algorithm

Abstract

The invention discloses a monocular camera object identification and positioning method based on a vector illumination influence removal algorithm, and the method comprises the steps of S1, collecting an image map through a robot, and carrying out illumination removal processing on the image map; S2, filtering the image map after illumination removal processing, and obtaining a filtered image; S3, performing color space conversion on the image, and obtaining a binary image according to the color threshold value of the target object; S4, eliminating interferents outside target area, determining a target object, and obtaining the image coordinates of the target object; S5, judging whether the target object exists in the target area or not according to the image coordinates of the target object, and if not, returning to null and ending the identification and positioning; if yes, returning to the center coordinate of the target object, then adjusting the head angle and the body posture of a robot to enable the center coordinate of the target object to coincide with the center position of the image, then solving the distance from the target object to the robot according to a calculation model, and obtaining the recognition result of the target object.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a monocular camera object recognition and positioning method based on a vector light removal algorithm. Background technique [0002] The research on location recognition based on computer vision is a cutting-edge scientific and technological topic that has developed rapidly in recent years. It has many applications and very broad development prospects in many fields. However, illumination always has a great influence on the recognition of objects. The success rate of recognition of the same object varies greatly under different illumination intensities and different illumination angles. In terms of object positioning and ranging, equipment such as binocular cameras, RGBD depth cameras, or laser radars is usually required, which are expensive and susceptible to interference from external factors. [0003] Therefore, it is necessary to develop a monocular camera object r...

AI Technical Summary

Problems solved by technology

However, illumination always has a great influence on the recognition of objects. For the same object, the success rate of recognition varies greatly under different illumination intensities and different illumination angles.

In terms of object positioning and distance measurement, binocular cameras, RGBD depth cameras or laser radars are usually required, which are expensive and susceptible to interference from external factors.

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