Sub-pixel positioning method based on particle swarm algorithm
A particle swarm algorithm and sub-pixel positioning technology, applied in the field of computer vision, can solve problems such as local optimality, and achieve the effect of improving search accuracy
Pending Publication Date: 2020-11-20
JILIN UNIV
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[0004] In order to solve the situation that the traditional method is easy to fall into the local optimum when searching for the whole pixel, a sub-pixel positioning method based on the particle swarm optimization algorithm is provided.
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[0041] see Figure 4 As shown, a sub-pixel positioning method based on particle swarm optimization algorithm, including the following steps:
[0042] S1: Use matlab to simulate the digital speckle image as the original image, and translate the original image (decimal units) to obtain the target image (see figure 2 shown);
[0043] S2: Select a point to be measured in the original image, and record the coordinates (x, y) of the point to be measured, and divide a 2R*2R size in the deformed speckle image with the coordinates (x, y) as the center As the target area, R is the search radius. In the original image, with the point to be measured as the center, a 2r*2r rectangular area is divided as the sample sub-area for calculating the correlation coefficient, where r is the sample sub-area radius;
[0044] S3: In the target area, randomly initialize n points as n particles randomly initialized in the particle swarm optimization algorithm. For each particle, divide a 2r*2r recta...
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The invention relates to a sub-pixel positioning method based on a particle swarm algorithm, which belongs to the field of computer vision, and comprises the following steps: simulating a digital speckle image as an original image by using matlab, and translating the original image to obtain a target image; selecting a to-be-measured point in the original image, calculating a correlation coefficient, finding an integer pixel coordinate point in the deformed speckle image by using a particle swarm algorithm, and solving integer pixel displacement according to the positioned integer pixel coordinate point; taking the whole pixel coordinate point as the center, carrying out the interpolation of the region through employing a bicubic interpolation algorithm, and then finding a point with the maximum correlation coefficient in the region after interpolation through employing a particle swarm algorithm; and for the point with the maximum correlation coefficient found in the previous step, calculating sub-pixel coordinates by using a quadratic polynomial fitting algorithm. According to the method, a particle swarm search algorithm is used, and in order to improve the sub-pixel search precision, a binary polynomial fitting algorithm and a bicubic interpolation method are combined, so that the final precision reaches 0.01-0.02 pixel.
Description
technical field [0001] The invention relates to the field of computer vision, in particular to a sub-pixel positioning method based on a particle swarm algorithm. Background technique [0002] In recent years, the deformation measurement method based on digital image correlation has become an eye-catching test method in the field of modern photomechanics, and its application fields are becoming more and more extensive. Since the emergence of digital image correlation (DIC), it has been widely used in the research of many disciplines, such as material mechanics, biomechanics, fracture mechanics, micro-nano strain measurement, macroscopic large-scale deformation measurement, performance testing of various new materials, etc. Compared with the traditional contact strain measurement technology, which has slow speed, limited range, and inflexible operation, the digital image correlation measurement method has the advantages of non-contact, high precision, full-field measurement, ...
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IPC IPC(8): G06T7/73G06T7/11G06T3/40G06F30/20G06N3/00
CPCG06T7/73G06T7/11G06T3/4007G06F30/20G06N3/006
Inventor 王世刚高鹏赵运来玄玉波季成旺
Owner JILIN UNIV