由于红外图像背景的复杂多变及环境对运动目标识别的干扰幅度增大等诸多因素的影响,导致红外图像中目标识别准确率非常低。针对该问题的出现,提出一种基于多特征融合的红外图像目标识别算法。该算法提取图像的颜色特征、运动和边缘特征,基于粒子滤波框架下对以上三种特征数据融合处理并应用于粒子权值计算。实验结果表明,该融合算法能够更加有效地提高红外图像目标在复杂多变环境下的鲁棒性和识别准确率等。

Due to the complex and varied background of the infrared image and the influence of the environment on the recognition of moving target recognition, the accuracy of target recognition in infrared images is very low. Aiming at the emergence of this problem, an infrared image target recognition algorithm based on multi-feature fusion is proposed. The algorithm extracts the color features, motion and edge features of the image, based on the particle filter framework, the above three feature data fusion processing is applied to the particle weight calculation. The experimental results show that the fusion algorithm can improve the robustness and recognition accuracy of infrared image targets in complex and variable environments.