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Graphic image sorting method based on genetic programming algorithm

A graphic image, genetic programming technology, applied in the field of image processing, can solve the problem of not being able to label label information for all image data

Active Publication Date: 2014-07-23
XIDIAN UNIV
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Problems solved by technology

However, with the development of the times, it is impossible to label all image data with label information. Therefore, text-based image classification has its own limitations.

Method used

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  • Graphic image sorting method based on genetic programming algorithm
  • Graphic image sorting method based on genetic programming algorithm
  • Graphic image sorting method based on genetic programming algorithm

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Embodiment Construction

[0048] The genetic programming algorithm deals with the problem of image classification, which can be abstracted as the problem of classifying the feature set of the image library.

[0049] The graphic image classification method based on the genetic programming algorithm designed by the present invention, see figure 1 , and its specific implementation steps are as follows:

[0050] (1) According to the images in the image library, randomly select 50% of the total number to form the training set images, wherein the number of images of each class is equal to half of the total number of the class in the image library;

[0051] (2) Set the operator set of the first stage terminator set crossover probability mutation probability population size Variable step factor step, number of iterations gen 1 ; the set of operators for the second stage terminator set mutation probability crossover probability Iteration times gen 2 , population size

[0052] (3) Using th...

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Abstract

The invention belongs to the technical field of image processing, and particularly discloses a graphic image sorting method based on a genetic programming algorithm. The method comprises the steps that (1) image feature sets and training feature sets are constructed; (2) first-stage relevant parameters are set; (3) the image features are extracted; (4) species are initialized and fitness is estimated; (5) individuals are subjected to the survival of the fittest, superior individuals are subjected to crossover and variation, and the fitness is estimated; (6) the individuals are subjected to partial searching; (7) the species are estimated, and if the crossover and variation operation is completed is judged; (8) the good species are selected, and if evolution is over is judged; (9) the species are again initialized according the new features; (10) the better species are selected for crossover and variation; (11) an image matching model is output according to the optimal individual, and an individual tree is decoded to obtain new image features. The training model generated through the method can effectively improve image sorting precision.

Description

technical field [0001] The invention relates to the technical field of image processing, in particular to a graphic image classification method based on a genetic programming algorithm, which can be applied to the classification of digital images. Background technique [0002] 80% of the information received by humans comes from visual or image information, including images, graphics, animations, videos, text data, etc. This is the most effective and important way of obtaining and exchanging information. With the popularity of computers, people are increasingly using computers to help humans acquire and process image information. Image processing, image analysis and image understanding, the organic combination of these three levels is called image engineering. [0003] Image classification can be divided into content-based image classification and text-based image classification. Text-based image classification technology adds relevant tags to each image. When classifying,...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06T7/00G06N3/12
Inventor 刘若辰焦李成杨振庚王爽公茂果李阳阳马文萍
Owner XIDIAN UNIV
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