Feature point extraction method based on multiple laser-assisted targets

Abstract

The invention provides a feature point extraction method based on multiple laser-assisted targets, belongs to the fields of image processing and computer vision detection, especially relates to a data processing method of laser-assisted multi-view data registration, and particularly discloses an extraction method based on a multiple laser-assisted target design and feature points. The method adopts a laser array projection laser strip construction registration target which is composed of multiple non-contact lasers, in the target, intersections of a laser grid are taken as the feature points of the registration, and a coordinate position of the target is extracted through a high-precision target feature point extraction algorithm. According to the feature point extraction method based on the multiple laser-assisted targets, the target based on the laser assistance is adopted, and better adaptability is achieved compared with an adhesive type target; by means of the method of determining a region of interest first and extracting the feature points accurately later, the precision and efficiency of extracting the feature points are effectively improved.

Description

technical field [0001] The invention belongs to the field of image processing and computer vision detection, and in particular relates to a method for processing image data in laser-assisted multi-view data splicing, specifically a method for target design and feature point extraction based on multiple laser-assisted methods. Background technique [0002] In multi-view data stitching, the design of the target and the precise extraction of feature points have an important impact on the stitching accuracy. At present, the commonly used splicing targets are roughly divided into three types: sticking type, placement type, and projection type. The sticking type and placement type are easy to block the shape information of the measured object, and the on-site adjustment is inconvenient, and the adaptability to harsh environments is poor. However, the commonly used projective splicing targets often have the problems of difficulty in feature point extraction and low precision. The ...

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Problems solved by technology

[0003] In July 2006, Sun Junhua and others published the article "Visual Measurement Data Stitching Method Based on Planar Baseline Target" in the journal "Journal of Mechanical Engineering". As the feature point of splicing, the target has high precision, but in the case of partial occlusion of the measured object, due to the uncertainty of the occlusion situation, the corner points of the grid often have mismatching situations, and the target cannot be measured with Requires flexible adjustment, poor adaptability to high temperature and other harsh industrial and mining

In April 2009, Liu Xiaoli and others published the article "Global Matching Method of Depth Data Using Marker Points" in the journal "Acta Optics Sinica", which proposed a method of pasting white circular marker points in the public field of view as stitching targets. Remove image noise through Gaussian filtering, use edge detection operator to achieve rough edge positioning, then further precisely position ellipse, and finally perform least square fitting on edge feature points to obtain sub-pixel positioning of the center of the circle, this method has relatively cumbersome pasting And clear the mark work, the point cloud of the pasted mark part is missing, and the disadvantages of easy damage to the surface of the measured object

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