Research on Image Matching Algorithm Based on Improved Whale Optimization Algorithm

Hui Chang
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Abstract

Aiming at the problems of low accuracy and slow speed of traditional image matching methods, an image matching method based on improved whale optimization algorithm is proposed to solve complex image matching problems. Firstly, nonlinear factor is used replace of linear factor in whale optimization algorithm to improve the global exploration ability of the algorithm and balance the exploration and development of whale optimization algorithm. Then, the improved whale optimization algorithm is transformed into a target matching process, and the feature extraction of image blocks is carried out by using histogram of oriented gradient to achieve accurate target matching. Finally, experiments show that the improved whale optimization algorithm shows good results in image matching.
基于改进鲸鱼优化算法的图像匹配算法研究
针对传统图像匹配方法精度低、速度慢的问题,提出了一种基于改进鲸鱼优化算法的图像匹配方法来解决复杂的图像匹配问题。首先,用非线性因子代替鲸鱼优化算法中的线性因子,提高算法的全局探索能力,平衡鲸鱼优化算法的探索与发展。然后,将改进的鲸鱼优化算法转化为目标匹配过程,利用有向梯度直方图对图像块进行特征提取,实现精确的目标匹配。最后,实验表明,改进的鲸鱼优化算法在图像匹配方面取得了良好的效果。
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