基于大数据分析技术的激光图像智能识别方法

Cong Li
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摘要

为了提高激光图像的识别效果,本研究设计了一种基于大数据分析技术的激光图像智能识别方法。在设置激光全息扫描装置和参数的基础上,利用视觉系统标定方法获得激光图像。为了避免激光图像识别过程中坐标系的限制,构造了具有一般属性的有理函数模型。然后,利用卷积神经网络输出激光图像的特征数据,利用Spark并行支持向量机算法完成激光图像的分类。最后,构建了基于大数据分析技术的SVM分类模型。输入纹理特征数据,快速输出激光图像的分类结果,然后根据概率分布实现激光图像的智能分类识别。实验结果表明,该方法能准确识别激光图像中的微小特征,识别结果具有较高的峰值信噪比和较高的识别精度。
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Intelligent recognition method of laser image based on big data analysis technology
In order to improve the recognition effect of laser images, this study designed an intelligent recognition method of laser images based on big data analysis technology. On the basis of setting up the laser holographic scanning device and parameters, the laser image is obtained by using the calibration method of vision system. In order to avoid the limitation of coordinate system in the process of laser image recognition, a rational function model with general attributes is constructed. Then, convolutional neural network is used to output the feature data of laser images, and Spark parallel support vector machine algorithm is used to complete the classification of laser images. Finally, the SVM classification model based on the big data analysis technology is constructed. The texture feature data can be input to quickly output the classification results of laser images, and then the intelligent classification and recognition of laser images can be realized according to the probability distribution. Experimental results show that this method can accurately identify the tiny features in laser images, and the recognition results have high peak signal-to-noise ratio and high recognition accuracy.
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