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Macula identification method based on genetic algorithm and simulated annealing algorithm

A simulated annealing algorithm and sunspot technology, applied in character and pattern recognition, genetic rules, gene models, etc., can solve problems such as automatic setting of single threshold and manual setting of threshold

Inactive Publication Date: 2018-05-08
KUNMING UNIV OF SCI & TECH
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  • Application Information

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Problems solved by technology

[0005] The invention provides a method for automatic identification of sunspot umbra and penumbra based on genetic algorithm and simulated annealing algorithm, and applies genetic algorithm and simulated annealing algorithm to self-adaptation based on optimal entropy fitness function of full sun image The selection of double thresholds is used to solve the problem of manually setting thresholds and automatically setting single thresholds in the traditional method of identifying sunspots

Method used

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  • Macula identification method based on genetic algorithm and simulated annealing algorithm
  • Macula identification method based on genetic algorithm and simulated annealing algorithm
  • Macula identification method based on genetic algorithm and simulated annealing algorithm

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Embodiment 1

[0027] Embodiment 1: as Figure 1-7 As shown, a sunspot identification method based on genetic algorithm and simulated annealing algorithm, first preprocesses the image, and performs dilation and erosion operations on the full-sun image to obtain a full-sun background image without sunspots. Subtract the expanded and eroded background image from the image to obtain a full-sun image with a uniform background, and perform mean smoothing filtering on the full-sun image with a uniform background to reduce noise; secondly, use the genetic algorithm to evolve two groups of threshold populations, after initializing the population and annealing parameters , adjust the order of the two thresholds of each population in ascending order, calculate the best entropy of each population, that is, fitness, randomly select two populations, and use the two pairs of chromosomes of the individuals of the two populations respectively 8-bit binary code, and use genetic operators to combine crossover...

Embodiment 2

[0035] Embodiment 2: as Figure 1-7 As shown, a sunspot identification method based on genetic algorithm and simulated annealing algorithm, first preprocesses the image, and performs dilation and erosion operations on the full-sun image to obtain a full-sun background image without sunspots. Subtract the expanded and eroded background image from the image to obtain a full-sun image with a uniform background, and perform mean smoothing filtering on the full-sun image with a uniform background to reduce noise; secondly, use the genetic algorithm to evolve two groups of threshold populations, after initializing the population and annealing parameters , adjust the order of the two thresholds of each population in ascending order, calculate the best entropy of each population, that is, the fitness, encode the two pairs of chromosomes of the individuals of the two populations with 8-bit binary, and use The genetic operator performs combined crossover and mutation on the code, and de...

Embodiment 3

[0059] Embodiment 3: as Figure 1-7 As shown, a method of sunspot identification based on genetic algorithm and simulated annealing algorithm, this embodiment is the same as embodiment 2, wherein:

[0060] In the step 1, the structural element t1 is a circle with a radius of 45; the structural element t2 is a matrix with a side length of 10.

[0061] In the step 2, the population size t3=16.

[0062] In the step 6, the range of t4 is 30.

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Abstract

The invention, which belongs to the astronomy technology and the image processing field, relates to a macula identification method based on a genetic algorithm and a simulated annealing algorithm. Pretreatment is carried out on an image; expansion and corrosion processing is carried out on a full-disk solar image respectively; a background image after expansion and corrosion is subtracted from thefull-disk solar image to obtain a full-disk solar image with the uniform background; mean smoothing filtering is carried out on the full-disk solar image with the uniform background and noise reduction is carried out; two groups of thresholds are evolved by using a genetic algorithm; the two groups of thresholds are processed by using a simulated annealing algorithm respectively to obtain a new population; whether an exit condition is met is determined; if so, two thresholds of an optimal entropy are found out from the population to segment the image; small area block removing processing is carried out on a segmentation result; and then a segmented image is marked and displayed.

Description

technical field [0001] The invention relates to a method for identifying sunspots based on a genetic algorithm and a simulated annealing algorithm, belonging to the fields of astronomical technology and image processing. Background technique [0002] Sunspots are one of the most fundamental and obvious activity in the sun's magnetic field. When sunspots are active, they will have a great impact on the Earth's magnetic field. For example, a magnetic storm will make the compass unable to indicate the direction correctly; the radio communication of airplanes, ships and artificial satellites will be seriously hindered. Therefore, there is an urgent need for a method that can accurately and efficiently identify sunspots on the sun's surface. This method is the basis and premise for studying and solving the impact of sunspots on the Earth's magnetic field and space weather. [0003] Identifying sunspots refers to segmenting sunspots from the full sun image, which is inseparable f...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/00G06K9/34G06N3/12
CPCG06N3/126G06V20/00G06V10/267
Inventor 杨云飞杨洪娟张艾丽付小娜梁波
Owner KUNMING UNIV OF SCI & TECH
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