Image Pattern Recognition Algorithm Based on Improved Genetic Algorithm

Abstract

Image recognition is an important part of artificial intelligence. In recent years, the technology has been developed rapidly and has been widely used in various fields. However, the existing image recognition technology is still not perfect, especially in the complex environment; the recognition accuracy still needs to be improved. To solve this problem, this paper proposes an image pattern recognition algorithm based on improved genetic algorithm. There are many algorithms for image recognition, but the mainstream algorithm is genetic algorithm. Genetic algorithm also shows its unique advantages in the field of image recognition. Aiming at the problem that the accuracy of existing image pattern recognition is not enough, this paper optimizes and improves the traditional genetic algorithm of image recognition. By improving the calculation method and genetic steps, the adaptability of genetic algorithm in the field of image recognition is improved. In order to further verify the actual effect of this algorithm, the corresponding comparative experiments are carried out. The experimental results show that the accuracy of the traditional genetic algorithm is 73.7%, and the improved genetic algorithm is 98.3%. The analysis shows that the improved genetic algorithm can better meet the actual needs of image pattern recognition. According to the characteristics of image recognition, the genetic algorithm can improve the accuracy and robustness of image recognition while ensuring the image quality.